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Kaggle AI Days 2025 - 5-Day AI Agents Intensive Course

Kaggle AI Days 2025: 5-Day AI Agents Intensive Course

Event Dates: November 10-14, 2025 Format: Online, Global Official Website: https://rsvp.withgoogle.com/events/google-ai-agents-intensive_2025 Kaggle Learn Guide: https://www.kaggle.com/learn-guide/5-day-agents

My Role and Contribution

Technical Leadership

  • Position: Course Lead for Day 3: Context Engineering & Memory
  • Name: TODO: [Insert full name]
  • Title: Developer Programs Engineer, Google Cloud
  • Responsibility: Led the curriculum development and implementation for context management in AI agents

Deliverables Created

  1. Colab Notebook 1: Short-term Memory Implementation
  2. Demonstrated session management techniques
  3. Practical examples using Google ADK SessionManagers

  4. TODO: [Add link to public Colab if available]

  5. Colab Notebook 2: Long-term Memory Implementation

  6. Showcased persistent memory patterns
  7. Integration with vector databases
  8. Production-ready memory architectures
  9. TODO: [Add link to public Colab if available]

Technical Content Delivered

  • Designed hands-on exercises for context engineering
  • Created practical implementations of memory systems
  • TODO: [Add details about live session participation if any]

Course Overview

This flagship Google AI course attracted over 420,000 registrations globally, following the success of the previous year's Gen AI Intensive Course. The course focused on building autonomous AI agents that go beyond simple chatbots.

5-Day Curriculum Structure

  1. Day 1: Introduction to Agents & Agentic Architectures
  2. Day 2: Agent Tools & Interoperability with MCP
  3. Day 3: Context Engineering & Memory (My Leadership Area)
  4. Day 4: Quality, Logging & Evaluation
  5. Day 5: Prototype to Production

Day 3 Focus: Context Engineering & Memory

As the Day 3 lead, I covered: - Short-term Memory: Conversation context and session management - Long-term Memory: Persistent knowledge and learning mechanisms - Memory Architecture Patterns: Best practices for production systems - Google ADK Integration: Practical implementation using ADK's memory components

Impact and Reach

  • Global Participation: TODO: [Insert actual participant numbers for Day 3]
  • Community Engagement: Active participation in Discord discussions
  • Capstone Projects: Participants used Day 3 concepts in their final projects

Technical Stack

  • Primary Framework: Google Agent Development Kit (ADK)
  • Language: Python
  • Tools: Colab notebooks, Gemini API, Vector databases
  • Platforms: Kaggle, YouTube (live sessions), Discord (community)

Professional Outcomes

  • Established expertise in AI agent memory systems
  • Contributed to Google's official AI education initiatives
  • TODO: [Add any recognition, badges, or certificates received]
  • TODO: [Add feedback metrics or participant testimonials if available]

Resources and Follow-up

  • Course Materials: Available on Kaggle Learn platform
  • Community: Ongoing discussions in Kaggle Discord
  • My Contributions: TODO: [Add links to your public notebooks/materials]
  • Future Engagements: TODO: [Add any planned follow-up workshops or courses]

Key Takeaways for Participants

Through my Day 3 curriculum, participants learned: 1. How to implement stateful AI agents using memory systems 2. Best practices for context management in production 3. Practical patterns for short-term and long-term memory 4. Integration techniques with Google ADK

This course represents Google's commitment to democratizing AI agent development, and I'm proud to have contributed to educating the next generation of AI developers.