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Goutham Ummadisetty

Jest członkiem od 2025

Liga złota

7283 pkt.
[DEPRECATED]-Google Cloud Computing Foundations: Cloud Computing Fundamentals - Polski Earned lut 4, 2026 EST
Introduction to Generative AI - Polski Earned lut 4, 2026 EST
Google Security Operations - Fundamentals Earned sty 8, 2026 EST
Google DeepMind: 03 Design And Train Neural Networks Earned lis 12, 2025 EST
Snowflake to BigQuery Migration Earned lis 12, 2025 EST
Generative AI Fundamentals Earned lis 12, 2025 EST
Introduction to AI Applications Earned lis 11, 2025 EST
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation Earned lis 11, 2025 EST
Model evaluation on Vertex AI Earned lis 3, 2025 EST
Integrate Agent Assist with Telephony and Chatbot Systems Earned paź 31, 2025 EDT
Create Data Stores for Gen AI Applications Earned paź 29, 2025 EDT
Introduction to Agent Assist and its GenAI Capabilities Earned paź 29, 2025 EDT

Szkolenie Podstawy przetwarzania danych w Google Cloud pozwoli osobom z niewielkim lub zerowym doświadczeniem z zakresu przetwarzania danych w chmurze szczegółowo zapoznać się z najważniejszymi pojęciami z zakresu podstaw chmury, big data i systemów uczących się. Zawiera także informacje o tym, gdzie i jak można wykorzystać Google Cloud. Po zakończeniu szkolenia uczestnicy będą potrafili wyjaśnić pojęcia dotyczące przetwarzania danych w chmurze, big data i systemów uczących się oraz zademonstrować wybrane umiejętności praktyczne. TTo szkolenie należy do serii szkoleń o nazwie Google Cloud Computing Foundations (Podstawy usług w chmurze Google). Szkolenia należy ukończyć w następującej kolejności: Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales Google Cloud Computing Foundatio…

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Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest generatywna AI oraz jakie są jej zastosowania. Szkolenie przedstawia również różnice pomiędzy tą technologią a tradycyjnymi systemami uczącymi się, a także narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.

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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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In this Google DeepMind course you will focus on the training process for machine learning models. You will learn how to spot and mitigate issues when training a model, such as overfitting and underfitting. In practical coding labs, you will implement and evaluate the multilayer perceptron for simple classification tasks. This will provide insights into the mechanics of training a neural network model and the backpropagation algorithm. Research case studies will demonstrate how neural networks power real-world models. Additionally, you will consider the broader social impacts of innovation by looking beyond immediate benefits to anticipate potential risks, safety concerns, and further-reaching societal consequences.

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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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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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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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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production. Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.

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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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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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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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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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