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HITIKA PADHI

Member since 2026

Gold League

2104 points
Build Your First Agent with Agent Development Kit (ADK) Earned Jun 17, 2026 EDT
Build Agents with Agent Development Kit (ADK) Earned Jun 17, 2026 EDT
Responsible AI for Developers: Fairness & Bias Earned Jun 17, 2026 EDT
AI Boost Bites: Presentation Scripts with Gemini Earned Jun 16, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation Earned Jun 16, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI Earned Jun 16, 2026 EDT
AI Boost Bites: Your Personal Feedback Agent Earned Jun 16, 2026 EDT
AI Boost Bites: Create Your Own Retro Arcade Game Earned May 18, 2026 EDT

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 Gemini platform. 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 Explore other content in the Gemini Agent Ready (GEAR) program.

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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 Agent Ready (GEAR) program.

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This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.

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This video covers how to use Gemini Advanced to research a topic, create a presentation outline, and then use Gemini in Google Docs to generate talking points.

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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 Agent Platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.

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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 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 video covers how to use a simple prompt in Gemini Canvas to build, customize, and share your own playable game, like Tic-Tac-Toe.

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