vegisetti kasiviswanath
Date d'abonnement : 2023
Ligue d'Argent
5179 points
Build Your First Agent with Agent Development Kit (ADK)
Earned mai 25, 2026 EDT
[Deprecated] AI Boost Bites: Your Personal AI Study Partner
Earned mai 11, 2026 EDT
[DEPRECATED] AI Boost Bites: Intro to NotebookLM
Earned mai 11, 2026 EDT
Build Agents with Agent Development Kit (ADK)
Earned mai 9, 2026 EDT
Google DeepMind: 01 Build Your Own Small Language Model
Earned avr. 5, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned mars 1, 2026 EST
AI Boost Bites: Prompting like a Pro with Google Workspace
Earned mars 1, 2026 EST
How to Use TPUs for Inference
Earned jan. 17, 2026 EST
Architecting an AI Inference Stack
Earned déc. 18, 2025 EST
AI Boost Bites: Your Personal Feedback Agent
Earned déc. 2, 2025 EST
Introduction to Responsible AI
Earned déc. 2, 2025 EST
Introduction to Large Language Models
Earned déc. 2, 2025 EST
Introduction to Generative AI
Earned déc. 2, 2025 EST
Turn your understanding of agents into practical reality by building, configuring, and running your first AI agent using Google’s Agent Development Kit (ADK).
In this hands-on course, you’ll set up a complete ADK development environment, create agents with both Python code and YAML configuration, and run them through multiple interfaces. You’ll also learn the core parameters that define agent behavior, taking what you learned in course 1 and applying it to working code.
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In this video, you'll learn to use NotebookLM as your personal AI study partner. Master the art of converting dense documentation into smart study guides, flashcards, and quizzes to ramp up quickly on new policies and industry research.
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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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Learn about how you can use Agent Development Kit (ADK) to build complex, production-ready AI agents. This course covers ADK’s open-source framework, moving from simple prompt engineering to a code-first, structured software development approach suitable for enterprise-grade, multi-agent systems. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.
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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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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 course is for developers interested in learning how to use TPUs for inference—from architecture to deployment, and how to solve common implementation challenges.
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This course is designed for developers looking to build an optimized AI inference stack on Google Cloud. Whether you’re working with GPUs or TPUs, you’ll explore the fundamental components of an inference stack, learn design principles for maximizing performance and reliability, and explore practical techniques to take your workloads from 0 to 1.
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This video covers how to build a personalized "Work with Me" agent using Gemini Gems, which helps streamline foundational feedback and makes your meetings more strategic and efficient.
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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.
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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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