Google Cloud Big Data and Machine Learning Fundamentals
Earned Sep 29, 2023 EDT
Security Practices with Google Security Operations - SIEM
Earned Sep 25, 2023 EDT
SAP on Google Cloud
Earned Sep 21, 2023 EDT
Preparing for Your Professional Cloud Security Engineer Journey
Earned Sep 6, 2023 EDT
This course will familiarize you with the core functionality of Chronicle, including the user interface, connections, and settings.
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Kursus ini meninjau fitur keamanan penting Model Armor dan membekali Anda untuk bekerja menggunakan layanan ini. Anda akan mempelajari risiko keamanan yang terkait dengan LLM dan cara Model Armor melindungi aplikasi AI Anda.
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Google Threat Intelligence memberikan visibilitas terhadap ancaman yang tak tertandingi dengan menghadirkan kecerdasan ancaman yang mendetail secara tepat waktu kepada tim keamanan di seluruh dunia. Kursus ini membahas berbagai kemampuan Google Threat Intelligence dan cara penggunaan umum produk ini oleh organisasi untuk memitigasi ancaman secara proaktif.
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In the context of a real-world use case, learn how to use Security Command Center’s virtual red teaming feature to identify risks. Then, learn how attack exposure scores help you prioritize issues and how risk reports keep stakeholders in the loop.
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Learn how to use NotebookLM to create a personalized study guide for the Professional Security Operations Engineer certification exam.
You'll review NotebookLM features, create a notebook in NotebookLM, and learn how to use a study guide to practice for a certification exam.
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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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Learn a variety of strategies and techniques to engineer effective prompts for generative models
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Learn how to leverage Gemini multimodal capabilities to process and generate text, images, and audio and to integrate Gemini through APIs to perform tasks such as content creation and summarization.
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This course delves into the complexities of assessing the quality of large language model outputs. It examines the challenges enterprises face due to the subjective and sometimes incorrect nature of LLM responses, including hallucinations and inconsistent results. The course introduces various evaluation metrics for different tasks like classification, text generation, and question answering, such as Accuracy, Precision, Recall, F1 score, ROUGE, BLEU, and Exact Match. It also explores evaluation methods offered by Vertex AI LLM Evaluation Services, including computation-based, autorater, and human evaluation, providing insights into their application and benefits. Finally, the module covers how to unit test LLM applications within Vertex AI.
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Data stores represent a simple way to make content available to many types of generative AI applications, including search applications, recommendations engines, Gemini Enterprise apps, Agent Development Kit agents, and apps built with Google Gen AI or LangChain SDKs. Connect data from many sources include Cloud Storage, Google Drive, chat apps, mail apps, ticketing systems, third-party file storage providers, Salesforce, and many more.
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Learn how to create Hybrid Search applications using Vertex AI Vertex Search to combine semantic searching with keyword search to return results based on both semantic meaning and keyword matching.
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Explore the four pillars of Enterprise Readiness in generative AI: data governance and privacy, security and compliance support, infrastructure reliability and sustainability, and responsible AI. You will also learn how these pillars address concerns about data privacy and security. Learn about customizing foundation models with your data while keeping your data safe using adapter layers, how to keep your AI models safe and compliant when deploying them across the world, and the multiple layers of encryption, rigorous controls, supply chain audits, and ongoing security testing that are built into Google Cloud. You will also learn about security controls such as VPC, customer-managed encryption keys, access transparency, and data residency zones. And explore enterprise controls, certifications, and responsible AI tooling available in Vertex AI to ensure your data remains secure and compliant with global regulations when deploying generative AI models.
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Evaluation is important at every step of your Gen AI development process. In this course you will learn how to evaluate gen AI agents built using agent frameworks.
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In this course, you will learn how to easily scale AI from laptop to Cloud by bringing Ray and Vertex AI together. You will learn how to create a Ray cluster, connect to it, and run some simple Ray code. You will also learn how to integrate BigQuery seamlessly with Ray data.
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Learn how to build your own Retrieval-Augmented Generation (RAG) solutions for greater control and flexibility than out-of-the-box implementations. Create a custom RAG solution using Vertex AI APIs, vector stores, and the LangChain framework.
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Initial deployment of Vertex AI Search and Gemini Enterprise apps takes only a few clicks, but getting the configurations right can elevate a deployment from a basic off-the-shelf app to an excellent custom search or recommendations experience.
In this course, you'll learn more about the many ways you can customize and improve search, recommendations, and Gemini Enterprise apps.
(Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)
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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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In this Google DeepMind course you will discover the mechanisms of the transformer architecture. You will investigate how transformer language models process prompts to make context-sensitive next-token predictions. Through practical activities you will explore the attention mechanism, visualize attention weights, and encounter advanced concepts like masked attention and multi-head attention. You will also learn other techniques that are necessary to build neural networks that are well-suited to be used as language models. Finally, through activities on values, stakeholder mapping and community engagement, you will practice concrete tools for ensuring AI projects are developed with communities, not just for them.
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AI Applications provides built-in analytics for your Vertex AI Search and Gemini Enterprise apps. Learn what metrics are tracked and how to view them in this course.
(Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)
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This course dives into the world of media creation in Vertex AI using Nano Banana and Veo. Learn to design text and image-based prompts to produce high-quality, consistent images, and captivating, cinematic video clips. You'll also learn to refine generated assets using core editing functions. Finally, this course guides you through multi-tool workflow implementations for creative control and consistency, empowering you to transform images into video clips and leverage Gemini for prompt writing assistance and feedback.
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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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Pelajari BigQuery ML untuk Inferensi, mengapa Analis Data harus menggunakannya, kasus penggunaannya, dan model ML yang didukung. Anda juga akan mempelajari cara membuat dan mengelola model ML ini di BigQuery.
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This course explores how to implement a streaming analytics solution using Pub/Sub.
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NotebookLM is an AI-powered collaborator that helps you do your best thinking. After uploading your documents, NotebookLM becomes an instant expert in those sources so you can read, take notes, and collaborate with it to refine and organize your ideas.
NotebookLM Pro gives you everything already included with NotebookLM, as well as higher utilization limits, access to premium features, and additional sharing options and analytics.
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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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Selesaikan badge keahlian tingkat menengah Rekayasa Data untuk Pembuatan Model Prediktif dengan BigQuery ML untuk menunjukkan keterampilan Anda dalam hal berikut: membangun pipeline transformasi data ke BigQuery dengan Dataprep by Trifacta; menggunakan Cloud Storage, Dataflow, dan BigQuery untuk membangun alur kerja ekstrak, transformasi, dan pemuatan (ETL); serta membangun model machine learning menggunakan BigQuery ML.
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Selesaikan badge keahlian tingkat menengah Membuat Model ML dengan BigQuery ML untuk menunjukkan keterampilan dalam hal berikut: membuat dan mengevaluasi model machine learning dengan BigQuery ML untuk membuat prediksi data.
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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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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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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 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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Selesaikan badge keahlian pengantar Menyiapkan Data untuk ML API di Google Cloud untuk menunjukkan keterampilan Anda dalam hal berikut: menghapus data dengan Dataprep by Trifacta, menjalankan pipeline data di Dataflow, membuat cluster dan menjalankan tugas Apache Spark di Dataproc, dan memanggil beberapa ML API, termasuk Cloud Natural Language API, Google Cloud Speech-to-Text API, dan Video Intelligence API.
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Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.
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This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.
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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.
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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.
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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 memperkenalkan konsep penafsiran dan transparansi AI. Kursus ini membahas pentingnya transparansi AI bagi developer dan engineer. Kursus ini juga mengeksplorasi metode dan alat praktis untuk membantu mencapai penafsiran dan transparansi, baik dalam model data maupun AI.
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Kursus ini memperkenalkan topik penting tentang privasi dan keamanan AI. Kursus ini mengeksplorasi metode dan alat praktis untuk menerapkan rekomendasi praktik privasi dan keamanan AI melalui penggunaan produk dan alat open source Google Cloud.
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Kursus ini memperkenalkan konsep responsible AI dan prinsip AI. Di dalamnya tercakup teknik untuk secara praktis mengidentifikasi keadilan dan bias serta memitigasi bias dalam praktik AI/ML. Kursus ini juga mengeksplorasi metode dan alat praktis untuk menerapkan praktik terbaik Responsible AI menggunakan produk Google Cloud dan alat open source.
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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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Complete the Improve customer and agent satisfaction with Agent Assist skill badge to demonstrate your proficiency in configuring basic conversational agents that can escalate actions to human agents, and configuring Agent Assist to help human agents with customer queries. You prove your knowledge in configuring Generators for summarization, classification and recommendation of tickets as well leverage tools such as Generative Knowledge Assist, to provide further context to human agents.
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 course will focus on Agent Assist, an AI-powered tool designed to enhance customer service interactions. In this course, you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the chat channel. You’ll learn how to take full advantage of Agent Assist from Gemini Enterprise for Customer Experience, and its range of Gen AI features and functionality.
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Connect conversational agents to external systems and APIs to expand what agents can do, designing an end-to-end system that is resilient, fault-tolerant and secure.
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Selamat datang di kursus TPU Cloud. Kita akan mempelajari kelebihan dan kekurangan TPU dalam berbagai skenario dan membandingkan beragam akselerator TPU untuk membantu Anda memilih akselerator yang tepat. Anda akan mempelajari bermacam strategi untuk memaksimalkan performa dan efisiensi model AI serta memahami pentingnya interoperabilitas GPU/TPU untuk alur kerja machine learning yang fleksibel. Melalui konten yang menarik dan demo praktis, kami akan memandu Anda langkah demi langkah dalam memanfaatkan TPU secara efektif.
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Penasaran dengan hardware canggih di balik AI? Modul ini menguraikan komputer AI yang dioptimalkan untuk performa, dan menunjukkan mengapa komputer tersebut sangat penting. Kita akan membahas bagaimana CPU, GPU, dan TPU membuat tugas AI menjadi sangat cepat, apa yang membuat masing-masing unik, dan bagaimana software AI memanfaatkannya secara maksimal. Pada akhirnya, Anda akan tahu persis cara memilih GPU yang tepat untuk project AI Anda, sehingga membantu Anda membuat pilihan cerdas untuk workload AI Anda.
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Siap mulai menggunakan AI Hypercomputer? Kursus ini akan membantu Anda. Kami akan membahas dasar-dasar terkait apa itu AI Hypercomputer dan cara AI Hypercomputer membantu AI dalam menangani workload AI. Anda akan mempelajari berbagai komponen di dalam hypercomputer, seperti GPU, TPU, dan CPU, serta menemukan cara memilih pendekatan deployment yang sesuai untuk kebutuhan Anda.
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This course equips learners with skills to govern data within their Google Workspace environment. Learners will explore data loss prevention rules in Gmail and Drive to prevent data leakage. They will then learn how to use Google Vault for data retention, preservation, and retrieval purposes. Next, they will learn how to configure data regions and export settings to align with regulations. Finally, learners will discover how to classify data using labels for enhanced organization and security.
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This course was designed to give learners a comprehensive understanding of Google Workspace core services. Learners will explore enabling, disabling, and configuring settings for these services, including Gmail, Calendar, Drive, Meet, Chat, and Docs. Next, they'll learn how to deploy and manage Gemini to empower their users. Finally, learners will examine use cases for AppSheet and Apps Script to automate tasks and extend the functionality of Google Workspace applications.
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This course empowers learners to secure their Google Workspace environment. Learners will implement strong password policies and two-step verification to govern user access. They will then utilize the security investigation tool to proactively identify and respond to security risks. Next, they will manage third-party app access and mobile devices to ensure security. Finally, learners will enforce email security and compliance measures to protect organizational data.
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This course was designed to provide an understanding of user and resource management in Google Workspace. Learners will explore the configuration of organizational units to align with their organization's needs. Additionally, learners will discover how to manage various types of Google Groups. They will also develop expertise in managing domain settings within Google Workspace. Finally, learners will master the optimization and structuring of resources within their Google Workspace environment.
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This course was designed to prepare Google Workspace Administrators to troubleshoot common Google Workspace issues. Learners will practice diagnosing and resolving problems in Gmail, Calendar, and Drive, and navigating the Admin console. They will also experience analyzing audit logs to troubleshoot security issues, and gathering information and using available resources to troubleshoot and report technical issues.
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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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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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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 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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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 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 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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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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This course introduces AI Applications. You will learn about the types of apps that you can create using AI Applications, the high-level steps that its data stores automate for you, and what advanced features can be enabled for Search apps.
(Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)
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Learn about the fundamental features of Security Command Center on Google Cloud. Spend time in this course to understand assets, detection and compliance. Security Command Center is a key part of your Google Cloud security journey, complete these modules and quiz to earn a completion badge.
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This course covers the baseline skills needed for the Google Security Operations Platform. The modules will cover specific actions and features that security engineers should become familiar with to start using the toolset.
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Take the next steps in working with the Chronicle Security Operations Platform. Build on fundamental knowledge to go deeper on cusotmization and tuning.
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Kursus ini memberikan ringkasan komprehensif terkait Google Cloud Security Command Center (SCC) Enterprise, yakni solusi Platform Perlindungan Aplikasi Berbasis Cloud (CNAPP) yang membantu organisasi mencegah, mendeteksi, dan merespons ancaman di seluruh layanan Google Cloud.
Anda akan mempelajari fitur-fitur utama SCC Enterprise, termasuk pendeteksian ancaman yang lebih baik, pengelolaan kerentanan yang mendalam, dan pengelolaan kasus yang terintegrasi.
Konsep dasar pengelolaan ancaman dan penilaian kerentanan juga akan dibahas, beserta demonstrasi praktis penggunaan SCC Enterprise untuk mengidentifikasi, menyelidiki, dan memperbaiki risiko keamanan di lingkungan multi-cloud Anda.
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This training aims to up-skill Google Cloud partners to deliver customer engagements through Delivery Navigator for available technical practice offerings. Learners will be able to navigate around the Delivery Navigator platform, select the desired method(s), and export the project WBS to a desired work management tool and Shared Google Drive. Sample artefacts are available through the Delivery Navigator methods and will be provided for reference.
Contents of this course will be updated as new features are released for the Delivery Navigator platform.
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Google Threat Intelligence provides unmatched visibility into threats by delivering detailed and timely threat intelligence to security teams around the world. This course covers the various capabilities of Google Threat Intelligence and common ways that organizations use this product to proactively mitigate threats.
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This course gives you a deep dive into the workflows of Tier 3 analysts.
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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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In this course, you'll learn to develop AI agents that answer questions using websites, documents, or structured data. You will explore 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 course gives you a deep dive into the workflows of Tier 1 and Tier 2 security analysts.
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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
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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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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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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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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 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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Welcome to the fourth course of the "Networking in Google Cloud" series: Network Security!
In this course, you'll dive into the services for safeguarding your Google Cloud network infrastructure.
The first module, Distributed Denial of Service (DDoS) Protection, covers how to fortify your network against Distributed Denial of Service (DDoS) attacks, ensuring uninterrupted availability of your services.
In the second module, Controlling Access to VPC Networks, you'll learn the network access control, enabling you to define permissions for who can access your resources and how.
Finally, in the third module, Advanced Security Monitoring and Analysis, we'll explore how to proactively detect and respond to potential threats, keeping your Google Cloud environment secure and resilient.
By the end of this course, you'll have a comprehensive understanding of Google Cloud network security.
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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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This course provides an introduction to databases and summarized the differences in the main database technologies. This course will also introduce you to Looker and how Looker scales as a modern data platform. In the lessons, you will build and maintain standard Looker data models and establish the foundation necessary to learn Looker's more advanced features.
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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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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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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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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 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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Discover how to use Colab Enterprise, a managed notebook environment that provides secure and compliant storage for your notebooks, that comes with two code-generation features: code complete and code gen. Create and use runtime templates in Vertex AI Workbench to give users access to more powerful compute resources while still maintaining control over the types of resources that are spun up. Share notebooks with other users and use versioning to keep track of changes to your notebooks. Learn how Colab Enterprise integrates BigQuery and Vertex AI. You will see how to pull data from BigQuery, use BQML to train a model, and have it all integrated with Vertex Model Registry. Explore how to fine-tune a Foundation model or generative AI model using the Vertex AI SDK. And, learn how to evaluate a tuned model and compare the results of multiple runs.
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Embark on a journey into the captivating world of embeddings! This course equips you with the theoretical and practical knowledge to harness their power in both product search and generative AI.
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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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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 implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataproc.
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Welcome to Optimize in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on optimization.
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Welcome to Design in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on schema design.
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This course explores the Geographic Information Systems (GIS), GIS Visualization, and machine learning enhancements to BigQuery.
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This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.
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This course explores how to implement a streaming analytics solution using Dataflow and BigQuery.
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Identify critical assets and their compliance requirements.
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This training course introduces Cloud NGFW. Topics include how Cloud NGFW provides centralized firewall management, centralized firewall visibility, advanced threat protection, and firewall insights.
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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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This course is for Google Cloud’s top 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. Those who complete the training and assessment will receive the Google Cloud Generative AI Trailblazer badge through Skills Boost.
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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.
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Kursus ini dikhususkan untuk membekali Anda dengan pengetahuan dan alat yang diperlukan guna mengungkap tantangan unik yang dihadapi oleh tim MLOps saat men-deploy dan mengelola model AI Generatif, serta mengeksplorasi cara Vertex AI memberdayakan tim AI dalam menyederhanakan proses MLOps dan mencapai keberhasilan dalam project AI Generatif.
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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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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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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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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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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 course explores the different products and capabilities of Gemini Enterprise for Customer Experience 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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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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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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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.
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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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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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(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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Kursus ini menunjukkan cara menggunakan model AI/ML untuk tugas-tugas AI generatif di BigQuery. Melalui kasus penggunaan praktis yang melibatkan pengelolaan hubungan pelanggan (CRM), Anda akan mempelajari alur kerja pemecahan masalah bisnis dengan model Gemini. Untuk memudahkan pemahaman, kursus ini juga menyediakan panduan langkah demi langkah melalui solusi coding menggunakan kueri SQL dan notebook Python.
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Welcome to the third course of the "Networking in Google Cloud" series: Network Architecture!
In this course, you will explore the fundamentals of designing efficient and scalable network architectures within Google Cloud.
In the first module, Introduction to Network Architecture, we'll start by introducing you to the core components and concepts of network architecture, including subnets, routes, firewalls, and load balancing.
Then in the second module, network topologies, we'll dive into various network topologies commonly used in Google Cloud, discussing their strengths, and weaknesses.
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Welcome to the second course in the networking and Google Cloud series routing and addressing.
In this course, we'll cover the central routing and addressing concepts that are relevant to Google Cloud's networking capabilities.
Module one will lay the foundation by exploring network routing and addressing in Google Cloud, covering key building blocks such as routing IPv4, bringing your own IP addresses and setting up cloud DNS. In Module two will shift our focus to private connection options, exploring use cases and methods for accessing Google and other services privately using internal IP addresses.
By the end of this course, you'll have a solid grasp of how to effectively route and address your network traffic within Google Cloud.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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Kursus ini memperkenalkan kemampuan AI dan machine learning (ML) Google Cloud, dengan fokus pada pengembangan project AI generatif dan prediktif. Kursus ini akan membahas berbagai teknologi, produk, dan alat yang tersedia di seluruh siklus proses data ke AI, yang memberdayakan data scientist, developer AI, dan engineer ML untuk meningkatkan keahlian mereka melalui latihan interaktif.
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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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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series.
In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area.
You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training.
This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.
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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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This course helps you structure your preparation for the Professional Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.
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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 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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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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In this course, we’ll show you how organizations are aligning their BI strategy to most effectively achieve business outcomes with Looker. We'll follow four iterative steps: Plan, Build, Launch, Grow, and provide resources to take into your own services delivery to build Looker with the goal of achieving business outcomes.
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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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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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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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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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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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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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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
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This course explores how to leverage Looker to create data experiences and gain insights with modern business intelligence (BI) and reporting.
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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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Good news! There’s a new updated version of this learning path available for you!Open the new Professional Cloud DevOps Engineer Certification Learning Path to begin, once you’ve selected the new path all your current progress will be reflected in the new version.
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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Identity, Resource Manager, IAM, Virtual Private Cloud firewalls, Cloud Load Balancing, Cloud Peering, Cloud Interconnect, and VPC Service Controls.
This is the first course of the Security in Google Cloud series. After completing this course, enroll in the Security Best Practices in Google Cloud course.
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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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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.
Pelajari lebih lanjut
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
Good news! There’s a new updated version of this learning path available for you!Open the new Professional Cloud Security Engineer Certification Learning Path to begin, once you’ve selected the new path all your current progress will be reflected in the new version.
Pelajari lebih lanjut
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.
Pelajari lebih lanjut
Learn the technical aspects you need to know about Chronicle and how it can help you detect and action threats.
Pelajari lebih lanjut
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.
Pelajari lebih lanjut
This course helps learners prepare for the Professional Cloud Security Engineer (PCSE) Certification exam. Learners will be exposed to and engage with exam topics through a series of lectures, diagnostic questions, and knowledge checks. After completing this course, learners will have a personalized workbook that will guide them through the rest of their certification readiness journey.
[DEPRECATED] SOAR Fundamentals
Earned Des 9, 2025 EST
Model Armor: Mengamankan Deployment AI
Earned Des 5, 2025 EST
Google Threat Intelligence
Earned Des 5, 2025 EST
Security Command Center: Identify and Prioritize Risks
Earned Des 5, 2025 EST
Build a Certification Study Guide: PSOE Exam Prep
Earned Des 5, 2025 EST
Find, Explore and Deploy Model Garden Models
Earned Nov 7, 2025 EST
Engineer Effective Prompts for Generative Models
Earned Nov 7, 2025 EST
Explore Google's Gen AI Models
Earned Nov 7, 2025 EST
Model evaluation on Vertex AI
Earned Nov 7, 2025 EST
Create Data Stores for Gen AI Applications
Earned Nov 7, 2025 EST
Implement Hybrid Search
Earned Nov 5, 2025 EST
Enterprise Readiness in Generative AI
Earned Nov 4, 2025 EST
Evaluate ADK Agents with Vertex AI Gen AI Evaluation Service
Earned Nov 4, 2025 EST
Scale AI with Ray on Vertex AI
Earned Nov 4, 2025 EST
Implement RAG with Vertex AI
Earned Nov 4, 2025 EST
Vertex AI Search and Gemini Enterprise UI Configurations
Earned Nov 3, 2025 EST
How Google Does Machine Learning
Earned Nov 3, 2025 EST
Google DeepMind: 04 Discover The Transformer Architecture
Earned Nov 2, 2025 EST
Vertex AI Search and Gemini Enterprise Analytics
Earned Okt 20, 2025 EDT
Generate and Edit Media in Vertex AI
Earned Sep 17, 2025 EDT
Meningkatkan Produktivitas dengan Gemini in BigQuery
Earned Sep 16, 2025 EDT
Menggunakan BigQuery Machine Learning untuk Inferensi
Earned Sep 16, 2025 EDT
Data Warehousing for Partners: Stream Data with Pub/Sub
Earned Sep 16, 2025 EDT
Introduction to NotebookLM
Earned Sep 16, 2025 EDT
Azure Virtual Machines to Compute Engine
Earned Sep 15, 2025 EDT
Rekayasa Data untuk Pembuatan Model Prediktif dengan BigQuery ML
Earned Sep 14, 2025 EDT
Membuat Model ML dengan BigQuery ML
Earned Sep 14, 2025 EDT
Custom Search with Embeddings in Vertex AI
Earned Sep 14, 2025 EDT
Penelusuran Vektor dan Embedding
Earned Sep 14, 2025 EDT
Pengantar Vertex AI Studio
Earned Sep 14, 2025 EDT
Model Transformer dan Model BERT
Earned Sep 14, 2025 EDT
Menyiapkan Data untuk ML API di Google Cloud
Earned Sep 13, 2025 EDT
Build a Certification Study Guide: PMLE
Earned Sep 13, 2025 EDT
Working with Notebooks in Vertex AI
Earned Sep 11, 2025 EDT
Pengantar AI Generatif
Earned Sep 10, 2025 EDT
Pengantar Model Bahasa Besar
Earned Sep 10, 2025 EDT
Machine Learning Operations (MLOps) dengan Vertex AI: Evaluasi Model
Earned Sep 10, 2025 EDT
Responsible AI untuk Developer: Penafsiran & Transparansi
Earned Sep 10, 2025 EDT
Responsible AI untuk Developer: Privasi & Keamanan
Earned Sep 10, 2025 EDT
Responsible AI untuk Developer: Keadilan & Bias
Earned Sep 9, 2025 EDT
Membuat Aplikasi AI Generatif di Google Cloud
Earned Sep 9, 2025 EDT
Improve customer and agent satisfaction with Agent Assist
Earned Sep 4, 2025 EDT
Introduction to Agent Assist and its GenAI Capabilities
Earned Sep 4, 2025 EDT
Extend Conversational Agents Functionality with Webhooks and Tools
Earned Agu 15, 2025 EDT
Infrastruktur AI: TPU Cloud
Earned Agu 7, 2025 EDT
Infrastruktur AI: GPU Cloud
Earned Agu 7, 2025 EDT
Infrastruktur AI: Pengantar AI Hypercomputer
Earned Agu 7, 2025 EDT
Google Workspace Data Governance
Earned Agu 7, 2025 EDT
Google Workspace Core Services
Earned Agu 7, 2025 EDT
Google Workspace Security
Earned Agu 7, 2025 EDT
Google Workspace User and Resource Management
Earned Agu 7, 2025 EDT
Google Workspace Troubleshooting
Earned Agu 5, 2025 EDT
Snowflake to BigQuery Migration
Earned Jun 16, 2025 EDT
Improve Performance by Fine-Tuning Foundation Models
Earned Jun 15, 2025 EDT
AI Boost Bites: No-Code Sheets & Scripts
Earned Jun 13, 2025 EDT
AI Boost Bites: Amplify Exec Voices with AI
Earned Jun 13, 2025 EDT
AI Boost Bites: Exec Summaries with Gemini Gems
Earned Jun 13, 2025 EDT
AI Boost Bites: "Eat the Frog" with NotebookLM
Earned Jun 13, 2025 EDT
AI Boost Bites: Gemini Image-to-Sheets Hack
Earned Jun 13, 2025 EDT
AI Boost Bites: NotebookLM for Competitive Edge
Earned Jun 13, 2025 EDT
AI Boost Bites: TL;DR with Gemini in Docs & Drive
Earned Jun 13, 2025 EDT
AI Boost Bites: Customer insights with NotebookLM
Earned Jun 13, 2025 EDT
AI Boost Bites: Gemini Gems – Your ultimate marketing sidekick
Earned Jun 13, 2025 EDT
Gemini untuk Data Scientist dan Analis
Earned Jun 13, 2025 EDT
Introduction to AI Applications
Earned Mei 22, 2025 EDT
Security Command Center Fundamentals
Earned Mei 15, 2025 EDT
Google Security Operations - Fundamentals
Earned Mei 15, 2025 EDT
Google Security Operations - Deep Dive
Earned Mei 14, 2025 EDT
Memulai Security Command Center Enterprise
Earned Mei 14, 2025 EDT
Delivery Navigator for Partners
Earned Mei 14, 2025 EDT
DEPRECATED Google Threat Intelligence
Earned Mei 13, 2025 EDT
SecOps on GDC for Tier 3 Analysts
Earned Mei 10, 2025 EDT
Conversational Agents Quality Assurance and Deployment Lifecycle
Earned Mei 7, 2025 EDT
Extend CX Agents with Vertex AI Search data stores
Earned Mei 7, 2025 EDT
SecOps on GDC for Tier 1 and Tier 2 Analysts
Earned Apr 26, 2025 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Apr 23, 2025 EDT
Build Batch Data Pipelines on Google Cloud
Earned Apr 21, 2025 EDT
Chronicle SIEM Fundamentals
Earned Apr 17, 2025 EDT
Mandiant Fundamentals
Earned Apr 17, 2025 EDT
AI Generatif: Memahami Lanskap
Earned Apr 17, 2025 EDT
Agen AI Generatif: Mentransformasi Organisasi Anda
Earned Apr 17, 2025 EDT
Aplikasi AI Generatif: Mentransformasi Pekerjaan Anda
Earned Apr 17, 2025 EDT
AI Generatif: Memahami Konsep Dasar
Earned Apr 17, 2025 EDT
AI Generatif: Lebih dari Sekadar Chatbot
Earned Apr 17, 2025 EDT
Networking in Google Cloud: Network Security
Earned Apr 13, 2025 EDT
Men-deploy Sistem Multi-Agen dengan Agent Development Kit (ADK) dan Agent Engine
Earned Apr 10, 2025 EDT
The Modern Data Platform and LookML
Earned Mar 17, 2025 EDT
Natural Language Processing on Google Cloud
Earned Mar 10, 2025 EDT
Feature Engineering
Earned Mar 8, 2025 EST
Membuat Model Pemberian Teks pada Gambar
Earned Mar 8, 2025 EST
Production Machine Learning Systems
Earned Mar 8, 2025 EST
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Mar 7, 2025 EST
Launching into Machine Learning
Earned Mar 7, 2025 EST
Building AI with Colab Enterprise
Earned Mar 7, 2025 EST
Vector Search and Embeddings in Product Search
Earned Mar 2, 2025 EST
Membuat Embedding, Penelusuran Vektor, dan RAG dengan BigQuery
Earned Mar 2, 2025 EST
Document AI: Building a Custom Document Extractor
Earned Feb 27, 2025 EST
Data Warehousing for Partners: Process Data with Dataproc
Earned Feb 27, 2025 EST
Data Warehousing for Partners: Optimize in BigQuery
Earned Feb 27, 2025 EST
Data Warehousing for Partners: Design in BigQuery
Earned Feb 27, 2025 EST
Data Warehousing for Partners: BigQuery Extended Capabilities
Earned Feb 27, 2025 EST
Data Warehousing for Partners: Enable Google Cloud Customers
Earned Feb 27, 2025 EST
Data Warehousing for Partners: Streaming Analytics
Earned Feb 27, 2025 EST
Evaluate Your Cloud Next Generation Firewall Needs
Earned Feb 23, 2025 EST
Introduction to Cloud Next Generation Firewall
Earned Feb 23, 2025 EST
Unlocking the Power of Google Cloud Generative AI for Partners
Earned Feb 22, 2025 EST
Google Cloud Generative AI Trailblazer
Earned Feb 22, 2025 EST
Security Best Practices in Google Cloud
Earned Feb 22, 2025 EST
Machine Learning Operations (MLOps) untuk AI Generatif
Earned Feb 20, 2025 EST
Vertex AI Search for Commerce
Earned Feb 19, 2025 EST
Responsible AI: Menerapkan Prinsip AI dengan Google Cloud
Earned Feb 19, 2025 EST
Deploy Google Agentspace
Earned Feb 18, 2025 EST
Mempercepat Pertukaran Pengetahuan dengan Gemini Enterprise
Earned Feb 18, 2025 EST
Recommendations with AI Applications
Earned Feb 18, 2025 EST
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned Feb 18, 2025 EST
Generative Playbooks
Earned Feb 16, 2025 EST
Accelerate Your Creativity with Text-to-Image using Imagen
Earned Feb 16, 2025 EST
Customer Experience with Google AI Architecture
Earned Feb 13, 2025 EST
Conversational AI Voice and Chat Integrations
Earned Feb 12, 2025 EST
Building Complex Self-Service Experiences in Conversational Agents
Earned Feb 11, 2025 EST
Search with AI Applications
Earned Feb 1, 2025 EST
Bekerja dengan Model Gemini di BigQuery
Earned Jan 23, 2025 EST
Networking in Google Cloud: Network Architecture
Earned Okt 4, 2024 EDT
Networking in Google Cloud: Routing and Addressing
Earned Okt 4, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Sep 27, 2024 EDT
Pengantar AI dan Machine Learning di Google Cloud
Earned Jun 16, 2024 EDT
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned Jun 15, 2024 EDT
Machine Learning Operations (MLOps): Getting Started
Earned Jun 15, 2024 EDT
DEPRECATED Planning for a Google Workspace Deployment
Earned Jun 1, 2024 EDT
Gemini di Google Meet
Earned Mei 30, 2024 EDT
Preparing for Your Professional Cloud Network Engineer Journey
Earned Mei 16, 2024 EDT
Migrating VMware to Google Cloud VMware Engine
Earned Mei 16, 2024 EDT
Modernizing Mainframe Applications with Google Cloud
Earned Mei 16, 2024 EDT
Developing a Google SRE Culture
Earned Apr 12, 2024 EDT
Achieving Business Outcomes with Looker
Earned Apr 3, 2024 EDT
Digital Transformation with Google Cloud
Earned Mar 18, 2024 EDT
Trust and Security with Google Cloud
Earned Mar 18, 2024 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned Mar 18, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned Mar 18, 2024 EDT
Scaling with Google Cloud Operations
Earned Mar 17, 2024 EDT
Exploring Data Transformation with Google Cloud
Earned Mar 17, 2024 EDT
Analyzing and Visualizing Data in Looker
Earned Mar 17, 2024 EDT
Data Warehousing for Partners: Analyze Data with Looker
Earned Mar 16, 2024 EDT
BI Reporting: Looker Visualization on BigQuery
Earned Mar 16, 2024 EDT
Certification Learning Path: Professional Cloud DevOps Engineer
Earned Mar 13, 2024 EDT
Managing Security in Google Cloud
Earned Mar 1, 2024 EST
Gemini di Google Spreadsheet
Earned Jan 12, 2024 EST
Gemini di Google Dokumen
Earned Jan 12, 2024 EST
Gemini di Gmail
Earned Jan 12, 2024 EST
Pengantar Gemini untuk Google Workspace
Earned Jan 12, 2024 EST
Arsitektur Encoder-Decoder
Earned Des 28, 2023 EST
Mekanisme Atensi
Earned Des 28, 2023 EST
Pengantar Pembuatan Gambar
Earned Des 28, 2023 EST
Pengantar Responsible AI
Earned Des 22, 2023 EST
Certification Learning Path: Professional Cloud Security Engineer
Earned Okt 8, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Sep 29, 2023 EDT
Security Practices with Google Security Operations - SIEM
Earned Sep 25, 2023 EDT
SAP on Google Cloud
Earned Sep 21, 2023 EDT
Preparing for Your Professional Cloud Security Engineer Journey
Earned Sep 6, 2023 EDT