Migrating Oracle Workloads to Google Cloud
Earned Apr 16, 2024 EDT
Modernization of Applications using Openshift on Google Cloud
Earned Apr 14, 2024 EDT
Custom Search with Embeddings in Vertex AI
Earned Apr 11, 2024 EDT
Rapid Migration & Modernization Program
Earned Apr 9, 2024 EDT
Penelusuran Vektor dan Embedding
Earned Apr 8, 2024 EDT
Machine Learning in the Enterprise
Earned Mar 25, 2024 EDT
How Google Does Machine Learning
Earned Mar 25, 2024 EDT
Modernizing Mainframe Applications with Google Cloud
Earned Mar 24, 2024 EDT
Trust and Security with Google Cloud
Earned Mar 22, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned Mar 22, 2024 EDT
Generative AI Explorer : Vertex AI
Earned Mar 19, 2024 EDT
Generative AI for Business Leaders
Earned Mar 7, 2024 EST
Generative AI Fundamentals
Earned Agu 17, 2023 EDT
Scaling with Google Cloud Operations
Earned Jul 19, 2023 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned Jul 19, 2023 EDT
Exploring Data Transformation with Google Cloud
Earned Jul 19, 2023 EDT
Digital Transformation with Google Cloud
Earned Jul 19, 2023 EDT
Text Prompt Engineering Techniques
Earned Jul 14, 2023 EDT
Implementing Generative AI with Vertex AI
Earned Jul 13, 2023 EDT
Penjelajah AI Generatif - Vertex AI
Earned Jul 13, 2023 EDT
Responsible AI: Menerapkan Prinsip AI dengan Google Cloud
Earned Jul 13, 2023 EDT
Pengantar Vertex AI Studio
Earned Jun 12, 2023 EDT
Membuat Model Pemberian Teks pada Gambar
Earned Jun 11, 2023 EDT
Model Transformer dan Model BERT
Earned Jun 11, 2023 EDT
Arsitektur Encoder-Decoder
Earned Jun 11, 2023 EDT
Mekanisme Atensi
Earned Jun 11, 2023 EDT
Pengantar Pembuatan Gambar
Earned Jun 11, 2023 EDT
Generative AI Fundamentals - Bahasa Indonesia
Earned Jun 9, 2023 EDT
Pengantar Responsible AI
Earned Jun 9, 2023 EDT
Pengantar Model Bahasa Besar
Earned Jun 9, 2023 EDT
Pengantar AI Generatif
Earned Jun 9, 2023 EDT
Kursus akselerasi sesuai permintaan ini memperkenalkan peserta pada infrastruktur dan layanan platform yang komprehensif dan fleksibel yang disediakan oleh Google Cloud, dengan fokus pada Compute Engine. Melalui kombinasi video materi edukasi, demo, dan lab interaktif, peserta akan mengeksplorasi dan men-deploy berbagai elemen solusi, termasuk komponen infrastruktur seperti jaringan, virtual machine, dan layanan aplikasi. Anda akan mempelajari cara menggunakan Google Cloud melalui konsol dan Cloud Shell. Anda juga akan mempelajari peran arsitek cloud, pendekatan desain infrastruktur, dan konfigurasi networking virtual dengan Virtual Private Cloud (VPC), Project, Jaringan, Subnetwork, alamat IP, Rute, dan Aturan firewall.
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Model tuning is an effective way to customize large models to your tasks. It's a key step to improve the model's quality and efficiency. Model tuning provides benefits such as higher quality results for your specific tasks and increased model robustness. You learn some of the tuning options available in Vertex AI and when to use them.
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Model Garden is a model library that helps you discover, test, and deploy models from Google and Google partners. Learn how to explore the available models and select the right ones for your use case. And how to deploy and interact with Model Garden models through the Google Cloud console and APIs.
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This video covers how to create a 'project notebook' in NotebookLM by adding all relevant sources to build a central, searchable knowledge hub for your team.
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This video covers how to use NotebookLM for common marketing tasks like
analyzing customer feedback, conducting market research, and generating
content ideas.
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This video covers how to use the Video Overviews feature in NotebookLM to automatically generate a short explainer video based on your source documents.
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This video covers how to use the 'Discover Sources' feature in NotebookLM to find and import relevant web-based sources directly into your research project.
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This video covers how to use the Mind Maps feature in NotebookLM to automatically create a visual representation of your sources, helping you understand connections and key concepts.
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This video covers how to use NotebookLM as a personal research
assistant by adding sources, asking questions, and generating new content
formats based on your documents.
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This video covers how to use Gemini in Gmail to draft new emails,
refine their tone, respond with context from Drive files, and use smart
reply suggestions.
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This video covers how to use the 'Help me create' feature in Google Docs to generate a complete, formatted document by referencing content from other files in your Drive.
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This video covers five key ways to use Google's AI tools, including Gemini in Workspace, the Gemini app, and NotebookLM, to enhance your daily productivity.
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This video covers how to use Gemini in Gmail to summarize emails, find information, and draft replies, helping you manage your inbox more efficiently.
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This video covers how to use Gemini in Slides to automatically generate
meeting recaps and draft follow-up emails, which can streamline your
post-meeting workflow and save you time.
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This video covers how you can leverage Gemini's advanced AI capabilities within Google Sheets to effortlessly pull data and generate insights in minutes, all without the need for any technical or coding background.
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This video will cover how to leverage Gemini Gems to create authentic
social media posts in your leader's unique voice. Learn to overcome the
challenge of scaling executive social presence by training a Gem with
writing samples and clear instructions. Discover how to generate engaging
posts quickly, saving time while amplifying thought leadership and
ensuring authenticity.
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This video covers how you can create your own Brevity Gem to summarize and transform messy notes or long documents into clear, concise, executive-ready summaries.
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This video covers how to use Gemini and Apps Script to automate manual tasks across Google Workspace. You'll learn to prompt Gemini to generate Apps Script code that automatically drafts email reminders in Google Sheets for tasks not marked 'Complete.' Automate your workflow with little to no technical expertise, freeing up time for more important work and eliminating manual follow-ups.
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This video covers how you can leverage Notebook LM to "eat the frog" on your to-do list by automating complex tasks like summarizing legislation and mapping services, saving you hours of work.
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This video covers how to eliminate tedious manual data entry using Gemini. Learn how to take a picture or screenshot of data (from PDFs, paper, or images) and prompt Gemini to instantly convert it into a structured Google Sheet. Discover this simple hack to save countless hours transcribing data, turning Gemini into your personal data entry assistant. Just snap, prompt, and export!
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AI Boost Bites is a video series designed to help you leverage Google's AI tools in your daily work. Each episode, under 10 minutes, features a quick video demonstrating a real-world AI use case or topic. After the video, you'll get a challenge to apply what you've learned. It's an easy, interactive way to boost your AI skills and improve your productivity.
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This video will cover how to use NotebookLM to gather and analyze
publicly available information, combine it with internal documents, and
extract key competitive insights.
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This video covers how to personalize your Gemini results in Google
Workspace. Learn to incorporate documents and research papers directly
into your prompts using the "@" symbol to get more targeted and relevant
AI output tailored to your needs.
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This video covers how you can use Gemini to summarize long documents in Google Workspace, so you can quickly get the information you need and save time. You'll learn how to use Gemini to summarize entire documents or just selected text, as well as how to use Gemini in Drive to summarize across multiple files.
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This video covers prompt engineering fundamentals for effective AI communication. Learn a simple framework (Persona, Task, Context, Format) to craft clear prompts, getting better, faster results from Gemini in Google Workspace. Discover how to use natural language, be specific, and iterate for optimal AI assistance.
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This video will cover how you can leverage Gemini's advanced AI capabilities in Google Docs to brainstorm ideas, draft various marketing content, and collaborate with your team.
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This video covers how NotebookLM can revolutionize customer insight gathering from call or chat transcripts. You'll learn to upload PDF transcripts of hundreds of conversations (even multilingual ones!) and quickly extract key themes, trending topics, and actionable insights without listening for hours. Discover how to save findings, share notebooks, and even generate interactive podcast summaries of your data.
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This video covers how to create your own Gemini Gems, advanced AI capabilities that can automate repetitive tasks and supercharge your productivity.
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Complete the Build search and recommendations AI Applications skill badge to demonstrate your proficiency in deploying search and recommendation applications through AI Applications. Additionally, emphasis is placed on constructing a tailored Q&A system utilizing data stores.
Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content.
A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network.
When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!
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This lab tests your ability to develop a real-world Generative AI Q&A solution using a RAG framework. You will use Firestore as a vector database and deploy a Flask app as a user interface to query a food safety knowledge base.
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Complete the Edit images with Imagen skill badge to demonstrate your skills with Imagen's mask modes and editing modes to edit images according to certain prompts.
A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network.
When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!
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In this skill bagde, you will demonstrate your ability to use and compare models available in the Vertex AI Model Garden. You'll deploy a model to a Vertex AI Endpoint, query other models via their API, and use Vertex AI's Gen AI evaluation service to measure the performance of multiple models.
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Complete the Extend Gemini with controlled generation and Tool use skill badge to demonstrate your proficiency in connecting models to external tools and APIs. This allows models to augment their knowledge, extend their capabilities and interact with external systems to take actions such as sending an email.
A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network.
When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!"
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Dalam kursus ini, Anda akan mempelajari cara mengembangkan aplikasi menggunakan Flutter, yakni toolkit UI portabel dari Google, dan mengintegrasikan aplikasi dengan Gemini, yakni rangkaian produk model AI generatif Google. Anda juga akan menggunakan Vertex AI Agent Builder, yakni platform Google untuk membangun dan mengelola Agen dan aplikasi AI.
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Tingkatkan pengalaman navigasi situs Anda menggunakan AI generatif untuk memberikan pengalaman penelusuran yang lebih baik bagi pengguna. Di kursus ini, Anda akan mempelajari cara menggunakan Vertex AI Search untuk memberikan pengalaman penelusuran generatif kepada pengguna situs Anda, sehingga mereka dapat menemukan konten yang ditawarkan oleh situs tersebut. Sebagai editor situs, Anda juga akan belajar cara menggunakan AI generatif untuk menerjemahkan dan meningkatkan kualitas konten dengan cepat dan efisien menggunakan saran.
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Aplikasi AI generatif dapat mewujudkan pengalaman pengguna baru yang hampir tidak dimungkinkan sebelum ditemukannya model bahasa besar (LLM). Sebagai developer aplikasi, bagaimana cara menggunakan AI generatif untuk membangun aplikasi yang menarik dan canggih di Google Cloud?
Dalam kursus ini, Anda akan mempelajari aplikasi AI generatif dan cara Anda dapat menggunakan desain perintah serta retrieval-augmented generation (RAG) untuk membangun aplikasi yang canggih menggunakan LLM. Anda akan mempelajari arsitektur siap produksi yang dapat digunakan untuk aplikasi AI generatif dan Anda akan membangun aplikasi chat LLM berbasis RAG.
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Kursus ini membekali para praktisi machine learning dengan alat, teknik, dan praktik terbaik penting untuk mengevaluasi model AI generatif dan prediktif. Evaluasi model adalah disiplin ilmu yang sangat penting untuk memastikan sistem ML memberikan hasil yang andal, akurat, dan berperforma tinggi dalam produksi.
Peserta akan mendapatkan pemahaman yang mendalam mengenai berbagai metrik evaluasi, metodologi, dan penerapannya yang sesuai di berbagai jenis model dan tugas. Kursus ini akan berfokus pada tantangan unik yang dibuat oleh model AI generatif dan memberikan strategi untuk mengatasinya secara efektif. Dengan memanfaatkan platform Vertex AI di Google Cloud, para peserta akan belajar cara mengimplementasikan proses evaluasi yang kuat untuk melakukan pemilihan, pengoptimalan, dan pemantauan berkelanjutan pada model.
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Kursus ini mengeksplorasi solusi Retrieval-Augmented Generation (RAG) di BigQuery untuk memitigasi halusinasi AI. Kursus ini akan memperkenalkan alur kerja RAG yang mencakup pembuatan embedding, penelusuran ruang vektor, dan pembuatan jawaban yang lebih baik. Kursus ini akan menjelaskan alasan konseptual di balik langkah-langkah ini dan implementasi praktisnya dengan BigQuery. Di akhir kursus, peserta akan dapat membangun pipeline RAG menggunakan BigQuery dan model AI generatif seperti Gemini dan model embedding untuk menangani kasus penggunaan halusinasi AI mereka sendiri.
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An AI-driven Contact Center as a Service (CCaaS) solution that is built natively on Google Cloud. The Implementation course provides Partners with essential training about the delivery of key features and functionality. The course explores how to leverage your key understanding of the product into successful customer implementation engagements with tips, best practices, guides, and more.
Note: This product was previously called Contact Center AI (CCAI) Platform you may see references to that name still in the course, however the course is technically correct.
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Configure and Maintain CCaaS as an Admin is a course that provides end users with essential learning about the core features, functionality, reporting, and configuration information most relevant to the role. This course is most appropriate for those who perform administrative functions to support the operation of the contact center as well as analyze, troubleshoot, and configure the platform to best meet the demands of customers. While this program will review some monitoring and reporting aspects, those topics are explored in depth in the course titled, “Managing Functions and Reporting with CCaaS".
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Manage Functions and Reporting with CCaaS provides end-users with essential training about the core features, functionality, monitoring, reporting, and configuration information that is most relevant to the role. This course is most appropriate for those at the managerial level of the contact center who are tasked with monitoring the effectiveness, efficiency, and KPI attainment for all consumer interactions. While this program will review some aspects of settings and configuration options, the major focus is on reporting functionality in CCaaS.
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This course teaches contact center agents about the core agent features and functionality in Contact Center as a Service (CCaaS). CCaaS is a unified contact center platform that accelerates an organization's ability to leverage and deploy contact centers without relying on multiple technology providers. This course is most appropriate for those who handle consumer interactions via chat and call.
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Welcome to Hybrid Cloud Infrastructure Foundations with Anthos!
This is the first course of the Architecting Hybrid Cloud Infrastructure with Anthos path. Anthos enables you to build and manage modern applications, and gives you the freedom to choose where to run them. Anthos gives you one consistent experience in both your on-premises and cloud environments.
During this course, you will be presented with modules that will take you through skills that you will use as an architect or administrator running Anthos environments. The modules in this course include videos, hands-on labs, and links to helpful documentation.
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In this course, you'll learn about Kubernetes and Google Kubernetes Engine (GKE) security; logging and monitoring; and using Google Cloud managed storage and database services from within GKE.
This is the second course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Reliable Google Cloud Infrastructure: Design and Process course or the Hybrid Cloud Infrastructure Foundations with Anthos course.
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Agen AI Generatif: Mentransformasi Organisasi Anda adalah kursus kelima dan terakhir dari jalur pembelajaran Pemimpin AI Generatif. Kursus ini membahas cara organisasi menggunakan agen AI generatif kustom untuk membantu mengatasi tantangan bisnis tertentu. Anda akan mendapatkan praktik langsung dalam membangun agen AI generatif dasar, sambil mempelajari komponen agen ini, seperti model, loop penalaran, dan alat.
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Aplikasi AI Generatif: Mentransformasi Pekerjaan Anda adalah kursus keempat dari jalur pembelajaran Generative AI Leader. Kursus ini memperkenalkan aplikasi AI generatif Google, seperti Gemini untuk Workspace dan NotebookLM. Kursus ini memandu Anda memahami konsep seperti grounding, retrieval augmented generation, menyusun perintah yang efektif, dan membangun alur kerja otomatis.
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AI Generatif: Memahami Lanskap adalah kursus ketiga dari alur pembelajaran Generative AI Leader. AI generatif mengubah cara kita bekerja dan berinteraksi dengan dunia di sekitar kita. Namun, sebagai seorang pemimpin, bagaimana Anda dapat memanfaatkan kekuatan AI untuk mendorong hasil bisnis yang nyata? Dalam kursus ini, Anda akan mempelajari berbagai lapisan dalam membangun solusi AI generatif, penawaran Google Cloud, dan faktor yang perlu dipertimbangkan saat memilih solusi.
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AI Generatif: Memahami Konsep Dasar adalah kursus kedua dari alur pembelajaran Generative AI Leader. Dalam kursus ini, Anda akan mempelajari konsep dasar AI generatif. Anda akan mempelajari perbedaan antara AI, ML, dan AI generatif serta mempelajari bagaimana berbagai jenis data memungkinkan AI generatif mengatasi tantangan bisnis. Anda juga akan mendapatkan insight tentang strategi Google Cloud untuk mengatasi keterbatasan model dasar dan tantangan utama dalam pengembangan dan deployment AI yang bertanggung jawab dan aman.
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AI Generatif: Lebih dari Sekadar Chatbot adalah kursus pertama dari alur pembelajaran Generative AI Leader. Kursus ini tidak memiliki prasyarat. Kursus ini bertujuan untuk melampaui pemahaman dasar tentang chatbot guna mengeksplorasi potensi sebenarnya dari AI generatif untuk organisasi Anda. Anda akan mempelajari konsep seperti model dasar dan rekayasa perintah, yang penting untuk memanfaatkan kekuatan AI generatif. Kursus ini juga memandu Anda melalui pertimbangan penting yang harus Anda buat saat mengembangkan strategi AI generatif yang sukses untuk organisasi Anda.
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Dalam kursus ini, Anda akan mempelajari cara menggunakan Agent Development Kit Google untuk membangun sistem multi-agen yang kompleks. Anda akan membangun agen yang dilengkapi dengan berbagai alat. Anda juga akan menghubungkannya melalui hubungan dan alur induk-turunan untuk menentukan interaksi antara berbagai agen. Anda akan menjalankan agen secara lokal dan men-deploy-nya ke Agent Engine Vertex AI untuk dijalankan sebagai alur agen terkelola. Agent Engine akan menangani keputusan infrastruktur dan penskalaan resource.
Lab ini didasarkan pada versi pra-rilis produk ini. Lab ini mungkin mengalami jeda saat kami melakukan update pemeliharaan.
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The course explores advanced services such as machine learning, and operational topics such as application deployment, monitoring, and troubleshooting.
In addition, we’ll introduce GDC software upgrades, logging, billing, and cost monitoring.
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The course examines service resources or workload components that exist in projects. You’ll learn about Kubernetes in GDC, Artifact Registry, GDC Object Storage, Database Service, Networking, and Key Management and Security.
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This course provides an introduction to the GDC platform—which enables you to host, control, and manage infrastructure and services directly on your premises.
GDC air-gapped is one component of Google Distributed Cloud offering which aligns to Google’s digital sovereignty vision. It supports public-sector customers and commercial entities that have strict data residency, security or privacy requirements.
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This L300 course explores the intricacies of the hardware and networking infrastructure, examines the role of Kubernetes in container orchestration, and how to master the deployment process. The course emphasizes critical security aspects, guiding you through defense-in-depth design, zero-trust architecture, and essential operational security measures for protecting sensitive data. You'll also gain valuable insights into operational aspects, such as resource management, upgrades, and solutions tailored for GDC customers.
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This L200 course comprehensively explores GDC air-gapped's concepts, architecture, and operational aspects, equipping learners with the knowledge to deploy and manage this solution effectively. The course delves into topics such as the roles of vendors and partners, hardware and software components, zero trust security, multi-tenancy, support and operations, observability, Identity and Access Management, managed services, and the GDC Sandbox environment. Furthermore, the course provides insights into compliance and accreditation processes, ensuring learners understand the regulatory landscape and can navigate it successfully. By the end of this course, learners will have a solid understanding of GDC air-gapped and be prepared to leverage its capabilities for their organization's needs.
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In this course, you will learn about GDC air-gapped (previously known as GDC Hosted), an offering from Google Distributed Cloud. This course provides both a business and technical overview of GDC air-gapped, exploring its key features and target customers.
Participants will gain insights into GDC air-gapped's value proposition and learn how to effectively communicate its benefits to potential clients, enabling them to qualify for sales opportunities.
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Networking in Google cloud is a 6 part course series. Welcome to the first course of our six part course series, Networking in Google Cloud: Fundamentals.
This course provides a comprehensive overview of core networking concepts, including networking fundamentals, virtual private clouds (VPCs), and the sharing of VPC networks. Additionally, the course covers network logging and monitoring techniques.
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In this skill badge, you will demonstrate your ability to deploy Google Agentspace and set up data stores and actions. To learn these skills, we encourage you to take the course Accelerate Knowledge Exchange with Agentspace.
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This L300 course offers a comprehensive exploration of GDC connected, encompassing design, deployment, operations, and advanced networking. It explores the architecture, configuration, and management of GDC infrastructure, including server setup, control plane operations, and network connectivity. The course also covers operational aspects, like high availability, failover, and observability, along with advanced networking topics such as APIs, network functions, and plugins.
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This L200 course comprehensively explores GDC connected concepts, architecture, and operational aspects, equipping learners with the knowledge to deploy and manage this solution effectively. The course delves into topics such as its survivability features and best practices, security, networking, software stack, and hardware options. Furthermore, the course provides insights into its operating model. By the end of this course, learners will have a solid understanding of GDC connected and be prepared to leverage its capabilities for their organization's needs.
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In "Architecting with Google Kubernetes Engine- Workloads", you'll embark on a comprehensive journey into cloud-native application development. Throughout the learning experience, you'll explore Kubernetes operations, deployment management, GKE networking, and persistent storage. This is the first course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Architecting with Google Kubernetes Engine- Production course.
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In this course, "Architecting with Google Kubernetes Engine: Foundations," you get a review of the layout and principles of Google Cloud, followed by an introduction to creating and managing software containers and an introduction to the architecture of Kubernetes.
This is the first course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Architecting with Google Kubernetes Engine: Workloads course.
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This course is for deployment personnel of Google Cloud and its partner organizations who are tasked with managing cultural change and skill gaps of customers adopting Google Workspace, engaging sponsors and enlisting the support of customer stakeholders, communicating the anticipated changes to the customer and their users. It will guide you through the Workspace change management methodology and all phases of the customer journey.
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This course on workspace transformation guides participants through modules designed to optimize and transform business environments using Google Workspace. It covers the Google Workspace Customer Success Methodology, provisioning processes, authentication and system access, mail routing, migration strategies, and coexistence planning to ensure a seamless transition and effective implementation.
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This course equips app developers with the skills to integrate generative AI features into their applications using Firebase Genkit. You learn how to leverage Firebase Genkit's capabilities for backend flows and seamless model execution, all using Node.js. The course guides you through the entire process, from prototyping to production, providing a pattern for building next-generation AI-powered applications.
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This course provides comprehensive skills on VM migration, from the initial assessment through the final implementation through presentations, demonstrations, and whiteboard session.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Snowflake to BigQuery. Sample data will be used during the migration. Learners will complete several labs that focus on the process of transferring schema, data and related processes to corresponding Google Cloud products.There will be one or more challenge labs that will test the learners' understanding of the topics. "This learning path aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Snowflake to BigQuery.
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Dalam kursus ini, Anda akan belajar tentang data engineering on Google Cloud, peran dan tanggung jawab data engineer, dan bagaimana hal tersebut terhubung dengan penawaran yang disediakan oleh Google Cloud. Anda juga akan mempelajari cara untuk mengatasi tantangan terkait data engineering.
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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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Migration from Oracle to Cloud Spanner using HarbourBridge. This course describes an example scenario that uses sample data during the migration. This process includes using HarbourBridge for Assessment, Schema Conversion, Schema Transformation, Data Migration, and supporting tools for data validation.
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Dalam kursus ini, Anda akan mempelajari Google Vids, yakni aplikasi pembuatan dan pengeditan video online yang tersedia untuk pengguna Google Workspace tertentu. Melalui pelajaran dan demo, Anda akan belajar cara membuat dan menyampaikan cerita menarik melalui video di tempat kerja. Anda juga akan belajar cara mengintegrasikan media, klip audio dan video dengan mulus, menyesuaikan gaya, serta membagikan karya Anda dengan mudah.
Beberapa fitur Vids menggunakan AI generatif untuk membantu Anda bekerja dengan lebih efisien. Ingat, alat AI generatif seperti Gemini mungkin menyarankan informasi yang tidak akurat atau tidak pantas. Jangan mengandalkan fitur Gemini untuk mendapatkan saran medis, hukum, keuangan, atau saran profesional lainnya. Perlu juga diingat bahwa saran fitur Gemini tidak mewakili pandangan Google, dan tidak boleh dikaitkan dengan Google.
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Gemini untuk Google Workspace adalah add-on yang menyediakan akses ke fitur AI generatif bagi pengguna. Kursus ini mempelajari kemampuan Gemini di Google Drive menggunakan video pembelajaran, aktivitas langsung, dan contoh praktis. Di akhir kursus ini, Anda akan dibekali pengetahuan dan keterampilan untuk menggunakan Gemini di Google Drive dengan percaya diri demi meningkatkan kualitas alur kerja Anda.
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In this course, you will learn about GDC connected (previously known as GDC Edge), an offering from Google Distributed Cloud. This course provides both a business and technical overview of GDC connected, exploring its key features and target customers.
Participants will gain insights into GDC connected's value proposition and learn how to effectively communicate its benefits to potential clients, enabling them to qualify for sales opportunities.
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This course focuses on how you can leverage the Google Cloud Analytics and AI/ML offerings to integrate and innovate with SAP
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This course is the third part of the SAP on Google Cloud Platform learning path. Following the SAP on Google Cloud Foundations eLearning and the SAP on Google Cloud Self-paced labs. Participants should have completed these two components before. This course consists of hands-on labs that provide a holistic experience of optimally configuring SAP on Google Cloud. Participants will learn to configure SAP on Google Cloud, and what best practices are, leaving the course with actionable experience to configure SAP on Google Cloud and run SAP workloads on Google Cloud for their customers.
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Perform a migration from Oracle to BigQuery using SQL Translation and DataFlow using Sample Data. Learners will complete a quiz that focuses on the process of transferring both schema and data from an Oracle enterprise data warehouse to BigQuery.
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This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Oracle and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Oracle, you also learn about similarities and differences between Oracle and BigQuery to help you get started with data warehouses in BigQuery. After this course, you can continue your BigQuery journey by completing the skill badge quest titled Build and Optimize Data Warehouses with BigQuery.
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Kursus ini mengeksplorasi Gemini in BigQuery, yakni paket fitur yang didukung AI untuk membantu alur kerja data ke AI. Paket fitur ini meliputi eksplorasi dan persiapan data, pembuatan kode dan pemecahan masalah, serta penemuan dan visualisasi alur kerja. Melalui penjelasan konseptual, kasus penggunaan praktis, dan lab interaktif, kursus ini akan membantu para praktisi data dalam meningkatkan produktivitas mereka dan mempercepat pipeline pengembangan.
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Padukan keahlian Google di bidang penelusuran dan AI dengan Gemini Enterprise, alat canggih yang dirancang untuk membantu karyawan menemukan informasi spesifik dari penyimpanan dokumen, email, chat, sistem tiket, dan sumber data lain, semuanya dari satu kotak penelusuran. Asisten Gemini Enterprise juga dapat membantu Anda bertukar pikiran, melakukan riset, membuat kerangka dokumen, serta mengambil tindakan seperti mengundang rekan kerja ke acara kalender untuk mempercepat pekerjaan dan kolaborasi berbasis pengetahuan dalam berbagai bentuk.
(Perhatikan bahwa Gemini Enterprise sebelumnya bernama Google Agentspace, mungkin ada referensi ke nama produk sebelumnya dalam kursus ini.)
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Imagen provides a suite of generative AI tools to help you accelerate your creative workflows. This course provides you with demonstrations of all the key features currently found in Imagen.
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Do you want to keep your users engaged by suggesting content they'll love?
This course equips you with the skills to build a cutting-edge recommendations app using your own data with no prior machine learning knowledge. You learn to leverage AI Applications to build recommendation applications so that audiences can discover more personalized content, like what to watch or read next, with Google-quality results customized using optimization objectives.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Oracle to Cloud SQL using the Ora2Pg.
An example scenario using sample data will be used to demonstrate the migration. Learners will complete an assessment quiz that focuses on the process of transferring schema, data and related processes to corresponding Google Cloud products.
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This course educates partners on key concepts around deploying Google Cloud VMware Engine (GCVE) and leveraging HCX to migrate VMs from on-premises VMware to GCVE.
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This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Snowflake and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Snowflake, you also learn about similarities and differences between Snowflake and BigQuery to help you get started with data warehouses in BigQuery. After this course, you can continue your BigQuery journey by completing the skill badge quest titled Build and Optimize Data Warehouses with BigQuery.
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This workload aims to upskill Google Cloud partners to perform specific tasks for modernization using LookML on BigQuery. A proof-of-concept will take learners through the process of creating LookML visualizations on BigQuery. During this course, learners will be guided specifically on how to write Looker modeling language, also known as LookML and create semantic data models, and learn how LookML constructs SQL queries against BigQuery. At a high level, this course will focus on basic LookML to create and access BigQuery objects, and optimize BigQuery objects with LookML.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating workloads from Hadoop environments to corresponding Google Cloud services and hosted products. The following will addressed will be: The Hadoop ecosystem and products Hadoop architecture and post migration architectures to Google Cloud Assessment Data transfer options Workload migrations, namely: Spark to Dataproc Serverless, Apache Oozie to Composer (Airflow), and Hive to BigQuery Security and governance Logging and Monitoring
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Migration from AWS EC2 to Google Cloud Compute Engine using Migrate to Virtual Machines (v5) using demo VM(s). It provides a proof-of-concept that walks you through the process of replicating a VM to doing test cutover and final cutover of the VM.
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Migration from on-premises VMware to Google Cloud Compute Engine using Migrate to Virtual Machines (v5) using demo VM(s). It provides a proof-of-concept that walks you through the process of replicating a VM to doing test cutover and final cutover of the VM.
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Welcome to the course focusing on the Migration from Pivotal Cloud Foundry to Google Cloud. This program offers a practical demonstration that guides you through the step-by-step process of transitioning applications seamlessly between these two platforms.
Throughout this course, you'll engage in hands-on exercises and demos, providing a proof-of-concept journey.
This course provides insights into Pivotal Cloud Foundry and Tanzu Kubernetes Grid (TKG), and their roles in cloud infrastructure. It includes hands-on sessions for installing Tanzu CLI. You'll also learn to deploy management clusters efficiently, organize cloud resources, and create workload clusters.
Additionally, you will perform a workload migration from Tanzu Kubernetes Grid to Google Kubernetes Engine (GKE) and containerize an applications on Google Cloud.
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Migration from Azure to Google Cloud Compute Engine using Migrate to Virtual Machines (v5) using demo VM(s). It provides a proof-of-concept that walks you through the process of replicating a VM to doing test cutover and final cutover of the VM.
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Outline the key steps in publishing an API to deliver selective company information to applications created by external developers.
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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
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Bukan rahasia lagi bahwa machine learning adalah salah satu bidang yang berkembang paling cepat di ranah teknologi, dan Google Cloud Platform telah berperan penting dalam memajukan pengembangannya. Dengan berbagai API, GCP memiliki alat untuk hampir semua tugas machine learning. Dalam kursus pengantar ini, Anda akan melakukan praktik langsung dengan machine learning sebagaimana diterapkan pada pemrosesan bahasa, melalui serangkaian lab yang akan memungkinkan Anda mengekstrak entity dari teks, melakukan analisis sentimen dan sintaksis, serta menggunakan Speech to Text API untuk melakukan transkripsi.
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Big data, machine learning, dan kecerdasan buatan menjadi topik komputasi yang populer saat ini, tetapi bidang tersebut sangat terspesialisasi dan materi pengantarnya sulit diperoleh. Untungnya, Google Cloud menyediakan layanan yang mudah digunakan dalam bidang tersebut, dan melalui kursus tingkat pengantar ini, Anda dapat mengambil langkah pertama dengan alat seperti BigQuery, Cloud Speech API, dan Video Intelligence.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.
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In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.
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This skill badge course is designed to offer hands-on experience through labs, enabling participants to master Document AI for document processing and extraction tasks. By the end of the course, participants will be proficient in creating and testing Document AI processors, customizing document extraction using Document AI Workbench, and building custom processors to tackle real-world document processing challenges.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with building a Custom Doc Extractor using the Google Cloud AI solution. The following will be addressed:
Service: Document AI
Task: Extract fields
Processors: Custom Document Extractor and Document Splitter
Prediction: Using Endpoint to programmatically extract fields
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This course explores the quality assurance best practices and the tools available in Conversational Agents to ensure production grade quality during Conversational Agent development, as well as the key tenets for the creation of a robust end to end deployment lifecycle. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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This course explores the fundamentals of the feedback loop process for Conversational Agent development and introduces the native capabilities within Conversational Agents that support it. You will also learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents.
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In this course, you will learn the important role that different types of webhooks play in Conversational Agents development, and how to effectively integrate them into your routine configuration of a Conversational Agent. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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Discover flows in Conversational Agents and learn how to build deterministic chat and voice experiences with language models. Explore key concepts like drivers, intents, and entities, and how to use them to create conversational agents.
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This course explores the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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This course explores the best practices, methods and tools to programmatically lead CCAI virtual agent delivery. It includes a high level overview of the end to end journey for building and deploying a virtual agent, as well as the core tenets to create a strong delivery culture. Additionally, this course covers the best practices for workflow management, defect tracking, release management and post-release support to ensure optimal virtual agent performance.
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Welcome to "CCAI Operations and Implementation", the fourth course in the "Customer Experiences with Contact Center AI" series. In this course, learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale. In this course, you'll be introduced to Agent Assist and the technology it uses so you can delight your customers with the efficiencies and accuracy of services provided when customers require human agents, connectivity protocols, APIs, and platforms which you can use to create an integration between your virtual agent and the services already established for your business, Dialogflow's Environment Management tool for deployment of different versions of your virtual agent for various purposes, compliance measures and regulations you should be aware of when bringing your virtual agent to production, and you'll be given tips from virtua…
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Welcome to "Virtual Agent Development in Dialogflow CX for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series.
In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations using Dialogflow CX.
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Welcome to "Virtual Agent Development in Dialogflow CX for Software Devs", the third course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop more customized customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to more advanced and customized handling for virtual agent conversations that need to look up and convey dynamic data, and methods available to you for testing your virtual agent and logs which can be useful for understanding issues that arise.
This is an intermediate course, intended for learners with the following type of role:
Software developers: Codes computer software in a programming language (e.g., C++, Python, Javascript) and often using an SDK/API.
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Welcome to "CCAI Conversational Design Fundamentals", the first course in the "Customer Experiences with Contact Center AI" series.
In this course, learn how to design customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will be introduced to CCAI and its three pillars (Dialogflow, Agent Assist, and Insights), and the concepts behind conversational experiences and how the study of them influences the design of your virtual agent. After taking this course you will be prepared to take your virtual agent design to the next level of intelligent conversation.
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This course educates partners on key concepts of Google’s Migrate to Containers. It will cover planning, workload fitness for conversion, deployment with a processing cluster, and the migration process.
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In this course, you will learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.
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This course explores advanced technical considerations to optimize Webhook connectivity for comprehensive, end-to-end, Conversational Agent self-service experiences. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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This course will equip you with the tools to develop complex conversational experiences in Conversational Agents capable of identifying the user intent and routing it to the right self service flow.
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Explore the Generative AI features for Conversational Agents and how to incorporate them into stateful Flows.
Discover the possibilities with Generators, Generative Fallback, and Data Stores, as well as best practices and security settings for using these features.
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This course will equip you with the tools to develop complex conversational experiences in Conversational Agents capable of identifying the user intent and routing it to the right self service flow. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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Explore Playbooks and their implementation of the ReAct pattern for building Conversational Agents. You will learn how to construct a Playbook, set up goals and instructions to build a chatbot in natural language, and learn to test and deploy your solution.
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Learn about building conversational AI voice and chat integrations, including how telephony systems can connect with Google to enable phone-based interactions within the Conversational AI ecosystem. Explore key topics such as the differences between chat and voice conversations, the writing process for creating conversation scripts, and the beginning of the interrogative series and closing sequence.
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Learn which Mandiant products directly enhance or augment capabilities provided by Chronicle SIEM and SOAR and how those products integrate into our workflow.
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This course will provide you with an overview of SIEM technology to set the stage for the differentiation and expansion of capabilities that Chronicle SIEM provides.
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This course will familiarize you with the core functionality of Chronicle, including the user interface, connections, and settings.
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In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.
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Keamanan adalah fitur layanan Google Cloud yang tidak dapat dikompromikan, dan Google Cloud telah mengembangkan alat khusus untuk memastikan keamanan dan identitas di seluruh project Anda. Dalam kursus pengantar ini, Anda akan melakukan praktik langsung dengan Layanan Identity and Access Management (IAM) Google Cloud, yang merupakan layanan utama untuk mengelola akun pengguna dan virtual machine. Anda akan mendapatkan pengalaman dengan keamanan jaringan dengan menyediakan VPC dan VPN, serta mempelajari alat-alat yang tersedia untuk mendapatkan perlindungan dari ancaman keamanan dan kebocoran data.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This third course covers cloud automation and management tools and building secure networks.
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Dapatkan badge keahlian dengan menyelesaikan kursus Menyiapkan Lingkungan Pengembangan Aplikasi di Google Cloud, yang memungkinkan Anda mempelajari cara membangun dan menghubungkan infrastruktur cloud yang berpusat pada penyimpanan menggunakan kemampuan dasar teknologi berikut: Cloud Storage, Identity and Access Management, Cloud Functions, dan Pub/Sub.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Pelajari lebih lanjut
The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This first course provides an overview of cloud computing, ways to use Google Cloud, and different compute options.
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This workload aims to upskill Google Cloud partners to deploy and manage Google Backup and Disaster Recovery (BDR).
The following will be addressed:
the core components and business value of Google BDR,
the prerequisites before installing Google BDR,
the initial deployment of Google BDR,
creating and configuring components of a Backup Plan,
the components of a Backup Plan,
discovering VMware and Compute Engine VMs,
and protecting, backing up, and restoring VMs.
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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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In this course, you will learn about the various services Google Cloud offers for modernizing retail applications and infrastructure. Through a series of lecture content and hands-on labs, you will gain practical experience deploying cutting-edge retail and ecommerce solutions on Google Cloud.
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This course equips full-stack mobile and web developers with the skills to integrate generative AI features into their applications using LangChain. You'll learn how to leverage LangChain’s capabilities for backend flows and seamless model execution, all within the familiar environment of Python. The course guides you through the entire process, from prototyping to production, ensuring a smooth journey in building next-generation AI-powered applications.
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Learn how Gemini can revolutionize your ability to develop applications! This course helps developers go beyond the basics and learn how to integrate Gemini into their workflows.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production.
Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine.
This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.
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This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.
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Menyelesaikan badge keahlian tingkat menengah Menginspeksi Dokumen Multimedia dengan Multimodalitas Gemini dan RAG Multimodal untuk menunjukkan keterampilan dalam hal berikut ini: menggunakan prompt multimodal untuk mengekstrak informasi dari data teks dan visual dengan menghasilkan deskripsi video, dan mengambil informasi tambahan di luar video menggunakan multimodalitas dengan Gemini; membangun metadata dokumen yang berisi teks dan gambar dengan mendapatkan semua potongan teks yang relevan, dan mencetak kutipan dengan menggunakan Multimodal Retrieval Augmented Generation (RAG) dengan Gemini.
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This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models.
The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data.
The course also looks at practical issues that arise, for example, when one doesn't have enough data and how to incorporate the latest research findings into different models.
Learners will get hands-on practice building and optimizing their own image classification models on a variety of public datasets in the labs they will work on.
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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.
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This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
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Kursus ini memperkenalkan penawaran AI dan machine learning (ML) di Google Cloud yang membangun project AI prediktif dan generatif. Kursus ini akan membahas teknologi, produk, dan alat yang tersedia di seluruh siklus proses data ke AI, yang mencakup fondasi, pengembangan, dan solusi AI. Kursus ini bertujuan membantu data scientist, developer AI, dan engineer ML meningkatkan keterampilan dan pengetahuan mereka melalui pengalaman belajar yang menarik dan latihan praktik langsung.
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Selesaikan badge keahlian tingkat menengah Mempelajari AI Generatif dengan Gemini API di Vertex AI untuk menunjukkan keterampilan dalam hal berikut: pembuatan teks, analisis gambar dan video untuk peningkatan kualitas pembuatan konten, serta penerapan teknik panggilan fungsi dalam Gemini API. Temukan cara memanfaatkan teknik Gemini yang canggih, menjelajahi pembuatan konten multimodal, dan memperluas kemampuan project yang didukung AI.
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Selesaikan badge keahlian tingkat menengah Mengembangkan Aplikasi GenAI dengan Gemini dan Streamlit untuk menunjukkan keterampilan dalam hal berikut: membuat teks, menerapkan panggilan fungsi dengan Python SDK dan Gemini API, serta men-deploy aplikasi Streamlit dengan Cloud Run. Anda akan mempelajari berbagai cara memberikan perintah kepada Gemini untuk membuat teks, menggunakan Cloud Shell untuk menguji dan melakukan iterasi pada aplikasi Streamlit, lalu mengemasnya sebagai container Docker yang di-deploy di Cloud Run.
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In this course you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the chat channel.
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(This course was previously named Multimodal Prompt Engineering with Gemini and PaLM) This course teaches how to use Vertex AI Studio, a Google Cloud console tool for rapidly prototyping and testing generative AI models. You learn to test sample prompts, design your own prompts, and customize foundation models to handle tasks that meet your application's needs. Whether you are looking for text, chat, code, image or speech generative experiences Vertex AI Studio offers you an interface to work with and APIs to integrate your production application.
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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities, learn to identify high-impact use cases, and develop the skills to demonstrate and integrate these technologies seamlessly into client solutions and operations.
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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities and learn to identify high-impact use cases.
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Dalam kursus ini, Anda akan mempelajari bagaimana Gemini, kolaborator yang didukung AI generatif dari Google Cloud, membantu Anda menggunakan produk dan layanan Google untuk mengembangkan, menguji, men-deploy, dan mengelola aplikasi. Dengan bantuan Gemini, Anda belajar cara mengembangkan dan membangun aplikasi web, memperbaiki error dalam aplikasi, mengembangkan pengujian, dan mengkueri data. Dengan menggunakan lab interaktif, Anda akan melihat bagaimana Gemini meningkatkan siklus proses pengembangan software (SDLC).
Duet AI berganti nama menjadi Gemini, yang merupakan model generasi berikutnya dari kami.
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Dalam kursus ini, Anda akan mempelajari bagaimana Gemini, kolaborator yang didukung AI generatif dari Google Cloud, membantu engineer mengelola infrastruktur. Anda akan mempelajari cara memerintah Gemini untuk menemukan dan memahami log aplikasi, membuat cluster GKE, dan menyelidiki cara membuat lingkungan build. Dengan menggunakan lab interaktif, Anda akan melihat bagaimana Gemini meningkatkan alur kerja DevOps.
Duet AI berganti nama menjadi Gemini, yang merupakan model generasi berikutnya dari kami.
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Dalam kursus ini, Anda akan mempelajari cara Gemini, kolaborator yang didukung AI generatif dari Google Cloud, dalam membantu engineer jaringan membuat, mengupdate, dan memelihara jaringan VPC. Anda akan mempelajari cara memanfaatkan Gemini untuk memberikan panduan spesifik untuk tugas-tugas jaringan Anda, lebih dari yang ditawarkan mesin telusur. Dengan menggunakan lab interaktif, Anda akan melihat cara Gemini dalam mempermudah urusan Anda dengan jaringan VPC Google Cloud.
Duet AI berganti nama menjadi Gemini, yang merupakan model generasi berikutnya dari kami.
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Dalam kursus ini, Anda akan mempelajari bagaimana Gemini, kolaborator yang didukung AI generatif dari Google Cloud, membantu Anda mengamankan lingkungan dan resource cloud. Anda akan mempelajari cara men-deploy contoh workload ke dalam lingkungan di Google Cloud, mengidentifikasi kesalahan konfigurasi keamanan dengan Gemini, dan memperbaiki kesalahan konfigurasi keamanan dengan Gemini. Dengan menggunakan lab interaktif, Anda akan melihat bagaimana Gemini meningkatkan postur keamanan cloud.
Duet AI berganti nama menjadi Gemini, yang merupakan model generasi berikutnya dari kami.
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Dalam kursus ini, Anda akan mempelajari bagaimana Gemini, kolaborator yang didukung AI generatif dari Google Cloud, membantu menganalisis data pelanggan dan memprediksi penjualan produk. Anda juga akan mempelajari cara mengidentifikasi, mengategorikan, dan mengembangkan pelanggan baru menggunakan data pelanggan di BigQuery. Dengan menggunakan lab interaktif, Anda akan melihat bagaimana Gemini meningkatkan analisis data dan alur kerja machine learning.
Duet AI berganti nama menjadi Gemini, yang merupakan model generasi berikutnya dari kami.
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Dapatkan badge keahlian tingkat menengah dengan menyelesaikan kursus Membangun dan Men-Deploy Solusi Machine Learning di Vertex AI, tempat Anda akan belajar cara menggunakan platform Vertex AI Google Cloud, AutoML, dan layanan pelatihan kustom untuk melatih, mengevaluasi, menyesuaikan, menjelaskan, serta men-deploy model machine learning. Kursus badge keahlian ini diperuntukkan bagi Data Scientist dan Engineer Machine Learning profesional. Badge keahlian adalah badge digital eksklusif yang diberikan oleh Google Cloud sebagai pengakuan atas kemahiran Anda dalam menggunakan produk dan layanan Google Cloud serta menguji kemampuan Anda dalam menerapkan pengetahuan di lingkungan praktis yang interaktif. Selesaikan Badge keahlian ini, dan challenge lab penilaian akhir, untuk menerima badge digital yang dapat Anda bagikan ke jaringan Anda.
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This skill badge course is designed to offer hands-on experience through labs, enabling participants to migrate applications to the cloud using a "Rehost" strategy. Participants will learn essential tasks involved in migrating both frontend (.Net application) and backend (MySQL database) components to existing virtual machines. Through guided and challenge labs, participants will validate successful migrations, reinforcing their understanding of cloud application modernization concepts.
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This learning path aims to upskill Google Cloud partners to perform the specific tasks associated with the priority workload. Learners will discover the specific tasks in rehosting applications from on-premises to Google Cloud. It also aims to re-platform applications to run in GKE. Learners will perform the tasks of Migrating MySQL, Angular, and .NET applications from their on-premises machines to Google Cloud VM instances. Sample code will be used during the migration. Learners will complete a challenge lab that focuses on the critical steps in a rehosting exercise - copying over code for the back-end, front-end, and middle-tier applications and validating that the applications have been migrated correctly. Learners will also complete a challenge lab that focuses on the critical steps in a re-platforming exercise - creating back-end, front-end, and middle-tier Docker images, deploying the same in the GKE cluster, and validating that the application has been deployed correctly.
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Dalam kursus ini, Anda akan mempelajari bagaimana Gemini, kolaborator yang didukung AI generatif dari Google Cloud, membantu administrator menyediakan infrastruktur. Anda akan mempelajari cara memerintah Gemini untuk menjelaskan infrastruktur, men-deploy cluster GKE, dan memperbarui infrastruktur yang ada. Dengan menggunakan lab interaktif, Anda akan melihat bagaimana Gemini meningkatkan alur kerja deployment GKE.
Duet AI berganti nama menjadi Gemini, yang merupakan model generasi berikutnya dari kami.
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Dalam kursus ini, Anda akan mempelajari cara Gemini, kolaborator berteknologi AI generatif dari Google Cloud, membantu developer membangun aplikasi. Anda akan mempelajari cara memanfaatkan Gemini untuk menjelaskan kode, merekomendasikan layanan Google Cloud, dan membuat kode untuk aplikasi Anda. Dengan lab interaktif, Anda akan merasakan peningkatan alur kerja pengembangan aplikasi menggunakan Gemini.
Duet AI berganti nama menjadi Gemini, yang merupakan model generasi berikutnya dari kami.
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This on-demand course provides partners the skills required to design, deploy, and monitor Vertail AI Search for Commerce solutions including retail search and recommendation AI for enterprise customers.
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This skill badge course is designed to offer hands-on experience through labs, guiding participants in gaining practical expertise in modernizing Java applications on the Google Cloud.
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This course aims to upskill Google Cloud partners to perform specific tasks in rehosting applications from on-premise to Google Cloud. It also aims to re-platform applications to run in GKE. Learners will perform the tasks of Migrating MySQL, Angular, and Java applications from their on-premise machines to Google Cloud VM instances. Sample code will be used during the migration.
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This course explores the different products and capabilities of Customer Engagement Suite (CES) and Conversational agents. Additionally, it covers the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel.
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(Previously named "Developing apps with Vertex AI Agent Builder: Search". Please note there maybe instances in this course where previous product names and titles are used)
Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use AI Applications to integrate enterprise-grade generative AI search.
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In this course you will learn how Conversational AI Agent Assist can help distill complex customer interactions into concise and clear summaries. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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In this course you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the voice channel, as well as the options available for integration with other platforms in the Conversational AI ecosystem.
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Gemini untuk Google Workspace adalah add-on yang memberi pengguna akses ke fitur AI generatif. Kursus ini akan berfokus pada kemampuan Gemini di Google Meet. Melalui video pelajaran, aktivitas interaktif, dan contoh praktis, Anda akan mendapatkan pemahaman komprehensif terkait fitur-fitur Gemini di Google Meet. Anda akan mempelajari cara menggunakan Gemini untuk membuat gambar latar, meningkatkan kualitas video, dan menerjemahkan teks. Setelah menyelesaikan kursus ini, Anda akan memiliki pengetahuan dan keterampilan untuk menggunakan Gemini di Google Meet dengan percaya diri sehingga dapat memaksimalkan efektivitas konferensi video Anda.
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Gemini untuk Google Workspace adalah add-on yang menyediakan fitur AI generatif bagi pelanggan di Google Workspace. Dalam kursus mini ini, Anda akan mempelajari berbagai fitur penting di Gemini dan cara penggunaannya untuk meningkatkan produktivitas dan efisiensi di Google Slide.
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Gemini untuk Google Workspace adalah add-on yang menyediakan fitur AI generatif bagi pelanggan di Google Workspace. Dalam kursus mini ini, Anda akan mempelajari berbagai fitur penting di Gemini dan cara penggunaannya untuk meningkatkan produktivitas dan efisiensi di Google Spreadsheet.
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Gemini untuk Google Workspace adalah add-on yang menyediakan akses ke fitur AI generatif bagi pengguna. Kursus ini mempelajari kemampuan Gemini di Google Dokumen dengan menggunakan video pembelajaran, aktivitas langsung, dan contoh praktis. Anda akan mempelajari cara menggunakan Gemini untuk menghasilkan konten tertulis berdasarkan perintah. Anda juga akan mengeksplorasi penggunaan Gemini untuk mengedit teks yang telah ditulis, sehingga membantu Anda meningkatkan produktivitas secara keseluruhan. Di akhir kursus ini, Anda akan dibekali pengetahuan dan keterampilan untuk menggunakan Gemini di Google Dokumen dengan percaya diri demi meningkatkan kualitas tulisan Anda.
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Gemini untuk Google Workspace adalah add-on yang menyediakan fitur AI generatif bagi pelanggan di Google Workspace. Dalam kursus mini ini, Anda akan mempelajari berbagai fitur penting di Gemini dan cara penggunaannya untuk meningkatkan produktivitas dan efisiensi di Gmail.
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Gemini untuk Google Workspace adalah add-on yang menyediakan fitur AI generatif bagi pelanggan di Google Workspace. Dalam jalur pembelajaran ini, Anda akan mempelajari berbagai fitur penting di Gemini dan cara penggunaannya untuk meningkatkan produktivitas dan efisiensi di Google Workspace.
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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
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This course on Integrate Vertex AI Search and Conversation into Voice and Chat Apps is composed of a set of labs to give you a hands on experience to interacting with new Generative AI technologies. You will learn how to create end-to-end search and conversational experiences by following examples. These technologies complement predefined intent-based chat experiences created in Dialogflow with LLM-based, generative answers that can be based on your own data. Also, they allow you to porvide enterprise-grade search experiences for internal and external websites to search documents, structure data and public websites.
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In this course, you'll learn to develop generative agents that answer questions using websites, documents, or structured data. You will explore Vertex AI Applications and understand the advantages of data store agents, including their scalability and security.
You'll learn about different data store types and also discover how to connect data stores to agents and add personalization for enhanced responses.
Finally, you'll gain insights into common search configurations and troubleshooting techniques.
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This is an introductory course to all solutions in the Conversational AI portfolio and the Gen AI features that are available to transform them. The course also explores the business case around Conversational AI, and the use cases and user personas addressed by the solution. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.
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In this course you will learn the key architectural considerations that need to be taken into account when designing for the implementation of Conversational AI solutions. Please note Dialogflow CX was recently renamed to Conversational Agents and CCAI Insights was renamed to Conversational Insights.
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This is a introductory course to all solutions in the Contact Centre AI (CCAI) portfolio and the Generative AI features that are poised to transform them. The course also explores the CCAI go to market and engagement model, the business case around CCAI, as well as the use cases and user personas addressed by the solution.
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In this course, you'll use text embeddings for tasks like classification, outlier detection, text clustering and semantic search. You'll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) solutions, such as for question-answering systems, using Google Cloud's Vertex AI and Google Cloud databases.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of rehosting Oracle Workloads on Google Cloud.
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This course focuses on modernizing applications using OpenShift on Google Cloud. Throughout this course, you'll gain the skills necessary to describe and understand OpenShift and successfully re-platform it to Google Cloud.
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This course explores Google Cloud technologies to create and generate embeddings. Embeddings are numerical representations of text, images, video and audio, and play a pivotal role in many tasks that involve the identification of similar items, like Google searches, online shopping recommendations, and personalized music suggestions. Specifically, you’ll use embeddings for tasks like classification, outlier detection, clustering and semantic search.
You’ll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) systems and question-answering solutions, on your own proprietary data using Google Cloud’s Vertex AI.
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The Google Cloud Rapid Migration & Modernization Program (RaMP) is a holistic, end-to-end migration/modernization program that helps customers & partners leverage expertise and best practices, lower risk, control costs, and simplify a customer's path to cloud success. This course will give an overview of the program and some of the tools and best practices available to support customer migrations & modernizations.
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Menjelajahi teknologi, alat, dan aplikasi penelusuran yang didukung AI dalam kursus ini. Mempelajari penelusuran semantik dengan memanfaatkan embedding vektor, penelusuran campuran yang menggabungkan pendekatan semantik dan kata kunci, serta Retrieval-Augmented Generation (RAG) yang meminimalkan halusinasi AI sebagai agen AI yang di-grounding. Mendapatkan pengalaman praktis dengan Vertex AI Vector Search untuk membangun mesin telusur yang cerdas.
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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing.
The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.
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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models.
The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.
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This course enables system integrators and partners to understand the principles of automated migrations, plan legacy system migrations to Google Cloud leveraging G4 Platform, and execute a trial code conversion.
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As organizations move their data and applications to the cloud, they must address new security challenges. The Trust and Security with Google Cloud course explores the basics of cloud security, the value of Google Cloud's multilayered approach to infrastructure security, and how Google earns and maintains customer trust in the cloud.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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This content is deprecated. Please see the latest version of the course, here.
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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.
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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task.
Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. "Modernize Infrastructure and Applications with Google Cloud" explores these challenges and offers solutions to overcome them by using cloud technology.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences.
“Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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There's much excitement about cloud technology and digital transformation, but often many unanswered questions.
For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin?
If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.
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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
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This course will help ML Engineers, Developers, and Data Scientists implement Large Language Models for Generative AI use cases with Vertex AI. The first two modules of this course contain links to videos and prerequisite course materials that will build your knowledge foundation in Generative AI. Please do not skip these modules. The advanced modules in this course assume you have completed these earlier modules.
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Kursus Penjelajah AI Generatif - Vertex AI adalah sekumpulan lab yang membahas cara menggunakan AI Generatif di Google Cloud. Melalui lab ini, Anda akan mempelajari cara menggunakan model dalam rangkaian Vertex AI PaLM API, termasuk text-bison, chat-bison, dan textembedding-gecko. Anda juga akan mempelajari desain perintah, praktik terbaik, serta cara menggunakannya untuk pencarian ide, klasifikasi teks, ekstraksi teks, peringkasan teks, dan banyak lagi. Anda juga akan mempelajari cara menyesuaikan model dasar dengan melatihnya melalui pelatihan kustom Vertex AI dan men-deploy-nya ke endpoint Vertex AI.
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Seiring semakin meningkatnya penggunaan Kecerdasan Buatan dan Machine Learning di kalangan perusahaan, proses membangunnya secara bertanggung jawab juga menjadi semakin penting. Membicarakan responsible AI mungkin lebih mudah bagi banyak orang daripada mempraktikkannya. Jika Anda tertarik untuk mempelajari cara mengoperasionalkan responsible AI dalam organisasi Anda, kursus ini cocok untuk Anda.
Dalam kursus ini, Anda akan mempelajari bagaimana Google Cloud mengoperasionalkan responsible AI, dengan praktik terbaik dan pelajaran yang dapat dipetik. Hal ini berguna sebagai framework bagi Anda untuk membangun pendekatan responsible AI.
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Kursus ini memperkenalkan Vertex AI Studio, sebuah alat untuk berinteraksi dengan model AI generatif, membuat prototipe ide bisnis, dan meluncurkannya ke dalam produksi. Melalui kasus penggunaan yang imersif, pelajaran menarik, dan lab interaktif, Anda akan menjelajahi siklus proses dari perintah ke produk dan mempelajari cara memanfaatkan Vertex AI Studio untuk aplikasi multimodal Gemini, desain perintah, rekayasa perintah, dan tuning model. Tujuan kursus ini adalah agar Anda dapat memanfaatkan potensi AI generatif dalam project Anda dengan Vertex AI Studio.
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Kursus ini menjelaskan cara membuat model keterangan gambar menggunakan deep learning. Anda akan belajar tentang berbagai komponen model keterangan gambar, seperti encoder dan decoder, serta cara melatih dan mengevaluasi model. Pada akhir kursus ini, Anda akan dapat membuat model keterangan gambar Anda sendiri dan menggunakannya untuk menghasilkan teks bagi gambar.
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Kursus ini memperkenalkan Anda pada arsitektur Transformer dan model Representasi Encoder Dua Arah dari Transformer (Bidirectional Encoder Representations from Transformers atau BERT). Anda akan belajar tentang komponen utama arsitektur Transformer, seperti mekanisme self-attention, dan cara penggunaannya untuk membangun model BERT. Anda juga akan belajar tentang berbagai tugas yang dapat memanfaatkan BERT, seperti klasifikasi teks, menjawab pertanyaan, dan inferensi natural language. Kursus ini diperkirakan memakan waktu sekitar 45 menit untuk menyelesaikannya.
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Kursus ini memberi Anda sinopsis tentang arsitektur encoder-decoder, yang merupakan arsitektur machine learning yang canggih dan umum untuk tugas urutan-ke-urutan seperti terjemahan mesin, ringkasan teks, dan tanya jawab. Anda akan belajar tentang komponen utama arsitektur encoder-decoder serta cara melatih dan menyalurkan model ini. Dalam panduan lab yang sesuai, Anda akan membuat kode pada penerapan simpel arsitektur encoder-decoder di TensorFlow untuk pembuatan puisi dari awal.
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Dalam kursus ini Anda akan diperkenalkan dengan mekanisme atensi, yakni teknik efektif yang membuat jaringan neural berfokus pada bagian tertentu urutan input. Anda akan mempelajari cara kerja atensi, cara penggunaannya untuk meningkatkan performa berbagai tugas machine learning, termasuk terjemahan mesin, peringkasan teks, dan menjawab pertanyaan.
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Kursus ini memperkenalkan model difusi, yaitu kelompok model machine learning yang belakangan ini menunjukkan potensinya dalam ranah pembuatan gambar. Model difusi mengambil inspirasi dari fisika, khususnya termodinamika. Dalam beberapa tahun terakhir, model difusi menjadi populer baik di dunia industri maupun penelitian. Model difusi mendasari banyak alat dan model pembuatan gambar yang canggih di Google Cloud. Kursus ini memperkenalkan Anda pada teori yang melandasi model difusi dan cara melatih serta men-deploy-nya di Vertex AI.
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Dapatkan badge keahlian dengan menyelesaikan kursus Introduction to Generative AI, Introduction to Large Language Models, dan Introduction to Responsible AI. Dengan berhasil menyelesaikan kuis akhir, Anda membuktikan pemahaman Anda tentang konsep dasar AI generatif.
Badge keahlian adalah badge digital yang diberikan oleh Google Cloud sebagai pengakuan atas pengetahuan Anda tentang produk dan layanan Google Cloud. Pamerkan badge keahlian Anda dengan menampilkan profil Anda kepada publik dan menambahkannya ke profil media sosial Anda.
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Ini adalah kursus pengantar pembelajaran mikro yang dimaksudkan untuk menjelaskan responsible AI, alasan pentingnya responsible AI, dan cara Google mengimplementasikan responsible AI dalam produknya. Kursus ini juga memperkenalkan 7 prinsip AI Google.
Pelajari lebih lanjut
Ini adalah kursus pengantar pembelajaran mikro yang membahas definisi model bahasa besar (LLM), kasus penggunaannya, dan cara menggunakan prompt tuning untuk meningkatkan performa LLM. Kursus ini juga membahas beberapa alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.
Pelajari lebih lanjut
Ini adalah kursus pengantar pembelajaran mikro yang bertujuan untuk mendefinisikan AI Generatif, cara penggunaannya, dan perbedaannya dari metode machine learning konvensional. Kursus ini juga mencakup Alat-alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.
Infrastruktur Google Cloud yang Penting: Fondasi
Earned Okt 7, 2025 EDT
Improve Performance by Fine-Tuning Foundation Models
Earned Okt 6, 2025 EDT
Find, Explore and Deploy Model Garden Models
Earned Sep 27, 2025 EDT
AI Boost Bites: Project Notebooks
Earned Sep 17, 2025 EDT
AI Boost Bites: NotebookLM for Market Research
Earned Sep 17, 2025 EDT
AI Boost Bites: NotebookLM Video Overviews
Earned Sep 17, 2025 EDT
AI Boost Bites: Discover Sources in NotebookLM
Earned Sep 17, 2025 EDT
AI Boost Bites: NotebookLM Mind Maps
Earned Sep 16, 2025 EDT
AI Boost Bites: Intro to NotebookLM
Earned Sep 16, 2025 EDT
AI Boost Bites: Email Content Creation
Earned Sep 16, 2025 EDT
AI Boost Bites: Create Docs in Seconds
Earned Sep 9, 2025 EDT
AI Boost Bites: AI Power-Ups for Google Workspace
Earned Sep 4, 2025 EDT
AI Boost Bites: Tame Your Inbox with AI
Earned Sep 4, 2025 EDT
AI Boost Bites: Gemini Slide Summaries
Earned Sep 4, 2025 EDT
AI Boost Bites: No-Code Sheets & Scripts
Earned Sep 4, 2025 EDT
AI Boost Bites: Amplify Exec Voices with AI
Earned Sep 4, 2025 EDT
AI Boost Bites: Exec Summaries with Gemini Gems
Earned Sep 4, 2025 EDT
AI Boost Bites: Automate tasks with Gemini and Apps Script
Earned Sep 4, 2025 EDT
AI Boost Bites: "Eat the Frog" with NotebookLM
Earned Sep 4, 2025 EDT
AI Boost Bites: Gemini Image-to-Sheets Hack
Earned Sep 4, 2025 EDT
AI Boost Bites: Poke Holes in Your Strategy
Earned Sep 4, 2025 EDT
AI Boost Bites: NotebookLM for Competitive Edge
Earned Sep 4, 2025 EDT
AI Boost Bites: Personalization with customized prompts
Earned Sep 1, 2025 EDT
AI Boost Bites: TL;DR with Gemini in Docs & Drive
Earned Sep 1, 2025 EDT
AI Boost Bites: Prompting like a Pro with Google Workspace
Earned Sep 1, 2025 EDT
AI Boost Bites: Content Generation with Gemini Made Easy
Earned Agu 26, 2025 EDT
AI Boost Bites: Customer insights with NotebookLM
Earned Agu 26, 2025 EDT
AI Boost Bites: Gemini Gems – Your ultimate marketing sidekick
Earned Agu 26, 2025 EDT
Build search and recommendations applications with AI Applications
Earned Agu 11, 2025 EDT
Deploy a RAG application with vector search in Firestore
Earned Agu 11, 2025 EDT
Edit images with Imagen
Earned Jul 31, 2025 EDT
Deploy and Evaluate Model Garden Models
Earned Jul 30, 2025 EDT
Extend Gemini with controlled generation and Tool use
Earned Jul 30, 2025 EDT
Membangun Agen AI Generatif dengan Vertex AI dan Flutter
Earned Jul 30, 2025 EDT
Modernisasi Situs dengan AI Generatif di Google Cloud
Earned Jul 29, 2025 EDT
Membuat Aplikasi AI Generatif di Google Cloud
Earned Jul 21, 2025 EDT
Machine Learning Operations (MLOps) dengan Vertex AI: Evaluasi Model
Earned Jun 30, 2025 EDT
Membuat Embedding, Penelusuran Vektor, dan RAG dengan BigQuery
Earned Jun 26, 2025 EDT
Contact Center as a Service Implementation
Earned Jun 4, 2025 EDT
Configure and Maintain CCaaS as an Admin
Earned Mei 20, 2025 EDT
Manage Functions and Reporting with CCaaS
Earned Mei 20, 2025 EDT
Handle Consumer Interactions with CCaaS
Earned Mei 20, 2025 EDT
Hybrid Cloud Infrastructure Foundations with Anthos
Earned Mei 12, 2025 EDT
Architecting with Google Kubernetes Engine: Production
Earned Mei 12, 2025 EDT
Agen AI Generatif: Mentransformasi Organisasi Anda
Earned Apr 30, 2025 EDT
Aplikasi AI Generatif: Mentransformasi Pekerjaan Anda
Earned Apr 30, 2025 EDT
AI Generatif: Memahami Lanskap
Earned Apr 30, 2025 EDT
AI Generatif: Memahami Konsep Dasar
Earned Apr 22, 2025 EDT
AI Generatif: Lebih dari Sekadar Chatbot
Earned Apr 22, 2025 EDT
Men-deploy Sistem Multi-Agen dengan Agent Development Kit (ADK) dan Agent Engine
Earned Apr 21, 2025 EDT
AI Services and GDC Deployments and Operations
Earned Apr 14, 2025 EDT
Compute, Network, and Storage Services Configuration in GDC
Earned Apr 11, 2025 EDT
GDC Platform Introduction
Earned Apr 11, 2025 EDT
L300 Google Distributed Cloud air-gapped
Earned Apr 3, 2025 EDT
L200 Google Distributed Cloud air-gapped
Earned Mar 26, 2025 EDT
Introduction to Google Distributed Cloud air-gapped
Earned Mar 20, 2025 EDT
Networking in Google Cloud: Fundamentals
Earned Mar 19, 2025 EDT
Deploy Google Agentspace
Earned Mar 17, 2025 EDT
L300 Google Distributed Cloud connected
Earned Mar 10, 2025 EDT
L200 Google Distributed Cloud Connected
Earned Mar 10, 2025 EDT
Architecting with Google Kubernetes Engine: Workloads
Earned Mar 10, 2025 EDT
Architecting with Google Kubernetes Engine: Foundations
Earned Feb 25, 2025 EST
Change Management for Google Workspace
Earned Feb 14, 2025 EST
Workspace Transformation
Earned Feb 14, 2025 EST
Build Generative AI Apps with Firebase Genkit
Earned Feb 7, 2025 EST
VM Migration for Partners
Earned Feb 6, 2025 EST
Snowflake to BigQuery Migration
Earned Feb 6, 2025 EST
Pengantar Data Engineering di Google Cloud
Earned Feb 5, 2025 EST
Preparing for your Professional Data Engineer Journey
Earned Jan 30, 2025 EST
Oracle to Cloud Spanner
Earned Jan 29, 2025 EST
Membuat Video yang Menarik dengan Google Vids
Earned Jan 27, 2025 EST
Gemini di Google Drive
Earned Jan 27, 2025 EST
Introduction to Google Distributed Cloud connected
Earned Jan 27, 2025 EST
Analytics for SAP on Google Cloud
Earned Jan 15, 2025 EST
SAP on Google Cloud
Earned Jan 15, 2025 EST
Oracle to BigQuery Migration
Earned Jan 6, 2025 EST
BigQuery Fundamentals for Oracle Professionals
Earned Jan 6, 2025 EST
Meningkatkan Produktivitas dengan Gemini in BigQuery
Earned Des 31, 2024 EST
Mempercepat Pertukaran Pengetahuan dengan Gemini Enterprise
Earned Des 18, 2024 EST
Accelerate Your Creativity with Text-to-Image using Imagen
Earned Des 18, 2024 EST
Recommendations with AI Applications
Earned Des 13, 2024 EST
Oracle to Cloud SQL for PostgreSQL
Earned Des 6, 2024 EST
Migrating VMware to Google Cloud VMware Engine
Earned Des 6, 2024 EST
BigQuery Fundamentals for Snowflake Professionals
Earned Nov 14, 2024 EST
BI Reporting: Looker Visualization on BigQuery
Earned Nov 6, 2024 EST
Migrating Hadoop Workloads
Earned Nov 6, 2024 EST
AWS EC2 to Compute Engine
Earned Nov 6, 2024 EST
On-Premises VMware to Compute Engine
Earned Nov 6, 2024 EST
Migrating Pivotal Cloud Foundry (PCF) to Google Cloud
Earned Nov 6, 2024 EST
Azure Virtual Machines to Compute Engine
Earned Nov 6, 2024 EST
Google API products: A key to modern application development
Earned Okt 31, 2024 EDT
Build Streaming Data Pipelines on Google Cloud
Earned Okt 30, 2024 EDT
Pengantar ML: Pemrosesan Bahasa
Earned Okt 28, 2024 EDT
Dasar pengukuran: Data, ML, AI
Earned Okt 28, 2024 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned Okt 24, 2024 EDT
Baseline: Deploy & Develop
Earned Okt 22, 2024 EDT
Build Custom Processors with Document AI
Earned Okt 21, 2024 EDT
Document AI: Building a Custom Document Extractor
Earned Okt 18, 2024 EDT
Conversational Agents Quality Assurance and Deployment Lifecycle
Earned Okt 14, 2024 EDT
Performance Measurement
Earned Okt 4, 2024 EDT
Webhook fundamentals
Earned Okt 3, 2024 EDT
Stateful Flows
Earned Okt 3, 2024 EDT
Conversation Design Fundamentals
Earned Okt 1, 2024 EDT
DFCX Virtual Agent Delivery Framework
Earned Okt 1, 2024 EDT
CCAI Operations and Implementation
Earned Sep 25, 2024 EDT
Virtual Agent Development in Dialogflow CX for Citizen Devs
Earned Sep 23, 2024 EDT
Virtual Agent Development in Dialogflow CX for Software Devs
Earned Sep 20, 2024 EDT
Contact Center AI: Conversational Design Fundamentals
Earned Sep 20, 2024 EDT
Migrate to Containers using the Migration Assessment Tool
Earned Sep 17, 2024 EDT
Advanced Performance Measurement
Earned Sep 15, 2024 EDT
Advanced Webhook Concepts
Earned Sep 11, 2024 EDT
Building Complex Self-Service Experiences in Conversational Agents
Earned Sep 11, 2024 EDT
Incorporate Generative Features into Conversational Agent flows
Earned Sep 9, 2024 EDT
Building Complex Self-Service Experiences in Conversational Agents
Earned Sep 9, 2024 EDT
Generative Playbooks
Earned Sep 9, 2024 EDT
Conversational AI Voice and Chat Integrations
Earned Sep 8, 2024 EDT
Mandiant Fundamentals
Earned Agu 29, 2024 EDT
Chronicle SIEM Fundamentals
Earned Agu 29, 2024 EDT
SOAR Fundamentals
Earned Agu 29, 2024 EDT
Serverless Data Processing with Dataflow: Operations
Earned Agu 29, 2024 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network
Earned Agu 28, 2024 EDT
Dasar-Dasar Keamanan & Identitas
Earned Agu 26, 2024 EDT
Google Cloud Computing Foundations: Networking & Security in Google Cloud
Earned Agu 21, 2024 EDT
Menyiapkan Lingkungan Pengembangan Aplikasi di Google Cloud
Earned Agu 21, 2024 EDT
Google Cloud Computing Foundations: Infrastructure in Google Cloud
Earned Agu 19, 2024 EDT
Google Cloud Computing Foundations: Cloud Computing Fundamentals
Earned Agu 16, 2024 EDT
Google Backup and Disaster Recovery
Earned Agu 16, 2024 EDT
Serverless Data Processing with Dataflow: Foundations
Earned Agu 12, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Agu 12, 2024 EDT
Modernizing Retail and Ecommerce Solutions with Google Cloud
Earned Agu 12, 2024 EDT
Orchestrating Gen AI Applications with LangChain
Earned Agu 2, 2024 EDT
Improving developer velocity with Gemini Code Assist
Earned Jul 31, 2024 EDT
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned Jul 24, 2024 EDT
Machine Learning Operations (MLOps): Getting Started
Earned Jul 24, 2024 EDT
Recommendation Systems on Google Cloud
Earned Jul 24, 2024 EDT
Natural Language Processing on Google Cloud
Earned Jul 23, 2024 EDT
Menginspeksi Dokumen Multimedia dengan Multimodalitas Gemini dan RAG Multimodal
Earned Jul 19, 2024 EDT
Computer Vision Fundamentals with Google Cloud
Earned Jul 18, 2024 EDT
Production Machine Learning Systems
Earned Jul 14, 2024 EDT
Feature Engineering
Earned Jul 11, 2024 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Jul 11, 2024 EDT
Launching into Machine Learning
Earned Jul 9, 2024 EDT
Pengantar AI dan Machine Learning di Google Cloud
Earned Jul 2, 2024 EDT
Mempelajari AI Generatif dengan Gemini API di Vertex AI
Earned Jul 2, 2024 EDT
Mengembangkan Aplikasi GenAI dengan Gemini dan Streamlit
Earned Jul 2, 2024 EDT
Introduction to Agent Assist and its GenAI Capabilities
Earned Jul 1, 2024 EDT
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned Jun 24, 2024 EDT
Selling the Platform & Building Client Trust
Earned Jun 24, 2024 EDT
Unlocking the Power of Google Cloud Generative AI for Partners
Earned Jun 24, 2024 EDT
Gemini untuk SDLC menyeluruh
Earned Jun 17, 2024 EDT
Gemini untuk Engineer DevOps
Earned Jun 17, 2024 EDT
Gemini untuk Engineer Jaringan
Earned Jun 17, 2024 EDT
Gemini untuk Engineer Keamanan
Earned Jun 14, 2024 EDT
Gemini untuk Data Scientist dan Analis
Earned Jun 14, 2024 EDT
Membangun dan Men-Deploy Solusi Machine Learning di Vertex AI
Earned Jun 11, 2024 EDT
Modernize .Net Applications
Earned Jun 11, 2024 EDT
.NET Modernization
Earned Jun 10, 2024 EDT
Gemini untuk Arsitek Cloud
Earned Mei 31, 2024 EDT
Gemini untuk Developer Aplikasi
Earned Mei 31, 2024 EDT
Vertex AI Search for Commerce
Earned Mei 31, 2024 EDT
Modernize Java Applications
Earned Mei 31, 2024 EDT
Modernization of Java Applications for Google Cloud
Earned Mei 31, 2024 EDT
Introduction to CES and Conversational Agents
Earned Mei 22, 2024 EDT
Search with AI Applications
Earned Mei 17, 2024 EDT
Agent Summarization (Custom)
Earned Mei 17, 2024 EDT
Integrate Agent Assist with Telephony and Chatbot Systems
Earned Mei 17, 2024 EDT
Gemini di Google Meet
Earned Mei 17, 2024 EDT
Gemini di Google Slide
Earned Mei 17, 2024 EDT
Gemini di Google Spreadsheet
Earned Mei 17, 2024 EDT
Gemini di Google Dokumen
Earned Mei 17, 2024 EDT
Gemini di Gmail
Earned Mei 17, 2024 EDT
Pengantar Gemini untuk Google Workspace
Earned Mei 17, 2024 EDT
Text Prompt Engineering Techniques
Earned Mei 10, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Mei 10, 2024 EDT
Virtual FAQ with data store agents
Earned Mei 9, 2024 EDT
Intro to Conversational AI and Conversational AI Engagement Framework
Earned Apr 28, 2024 EDT
Customer Engagement Suite with Google AI Architecture
Earned Apr 19, 2024 EDT
Intro to CCAI and CCAI Engagement Framework
Earned Apr 19, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned Apr 16, 2024 EDT
Migrating Oracle Workloads to Google Cloud
Earned Apr 16, 2024 EDT
Modernization of Applications using Openshift on Google Cloud
Earned Apr 14, 2024 EDT
Custom Search with Embeddings in Vertex AI
Earned Apr 11, 2024 EDT
Rapid Migration & Modernization Program
Earned Apr 9, 2024 EDT
Penelusuran Vektor dan Embedding
Earned Apr 8, 2024 EDT
Machine Learning in the Enterprise
Earned Mar 25, 2024 EDT
How Google Does Machine Learning
Earned Mar 25, 2024 EDT
Modernizing Mainframe Applications with Google Cloud
Earned Mar 24, 2024 EDT
Trust and Security with Google Cloud
Earned Mar 22, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned Mar 22, 2024 EDT
Generative AI Explorer : Vertex AI
Earned Mar 19, 2024 EDT
Generative AI for Business Leaders
Earned Mar 7, 2024 EST
Generative AI Fundamentals
Earned Agu 17, 2023 EDT
Scaling with Google Cloud Operations
Earned Jul 19, 2023 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned Jul 19, 2023 EDT
Exploring Data Transformation with Google Cloud
Earned Jul 19, 2023 EDT
Digital Transformation with Google Cloud
Earned Jul 19, 2023 EDT
Text Prompt Engineering Techniques
Earned Jul 14, 2023 EDT
Implementing Generative AI with Vertex AI
Earned Jul 13, 2023 EDT
Penjelajah AI Generatif - Vertex AI
Earned Jul 13, 2023 EDT
Responsible AI: Menerapkan Prinsip AI dengan Google Cloud
Earned Jul 13, 2023 EDT
Pengantar Vertex AI Studio
Earned Jun 12, 2023 EDT
Membuat Model Pemberian Teks pada Gambar
Earned Jun 11, 2023 EDT
Model Transformer dan Model BERT
Earned Jun 11, 2023 EDT
Arsitektur Encoder-Decoder
Earned Jun 11, 2023 EDT
Mekanisme Atensi
Earned Jun 11, 2023 EDT
Pengantar Pembuatan Gambar
Earned Jun 11, 2023 EDT
Generative AI Fundamentals - Bahasa Indonesia
Earned Jun 9, 2023 EDT
Pengantar Responsible AI
Earned Jun 9, 2023 EDT
Pengantar Model Bahasa Besar
Earned Jun 9, 2023 EDT
Pengantar AI Generatif
Earned Jun 9, 2023 EDT