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Hara Madhav Talasila

Date d'abonnement : 2026

Ligue d'Argent

2329 points
AI Boost Bites: NotebookLM Mind Maps Earned fév. 24, 2026 EST
AI Boost Bites: NotebookLM for Competitive Edge Earned fév. 15, 2026 EST
AI Boost Bites: Discover Sources in NotebookLM Earned fév. 15, 2026 EST
Optimize Agent Behavior Earned fév. 15, 2026 EST
Build Your First Agent with Agent Development Kit (ADK) Earned fév. 11, 2026 EST
Agent Fundamentals Earned fév. 11, 2026 EST
Introduction to Generative AI Earned fév. 11, 2026 EST

This video covers how to use the Mind Maps feature in NotebookLM to automatically create a visual representation of your sources, helping you understand connections and key concepts.

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This video will cover how to use NotebookLM to gather and analyze publicly available information, combine it with internal documents, and extract key competitive insights.

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This video covers how to use the 'Discover Sources' feature in NotebookLM to find and import relevant web-based sources directly into your research project.

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You’ve built your first agent—now it’s time to take it further. In this course, you’ll advance your skills by learning how to turn a basic AI agent into a sophisticated, precise assistant—applying advanced instructions, model selection, planning capabilities, and structured output patterns. Join the community forum for questions and discussions

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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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AI Agents represent a major shift beyond traditional large language models (LLMs): instead of simply generating text-based solutions, they can also act autonomously to execute them. This course introduces the fundamentals of AI Agents, how they differ from LLM APIs, and where they add value in the real world. Based on Google’s agents whitepaper, it provides the theoretical foundation needed before writing your first lines of agent code—ideal for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior (and not just text generation). Join the community forum for questions and discussions.

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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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