It’s a 5-day online course on November 11 - 15 designed to help you deeply understand some of the fundamental technologies and techniques behind Generative AI. Created by a team of Google’s ML researchers and engineers, this program includes both conceptual deep dives and hands-on coding examples so you can tackle new Gen AI projects with confidence.
How does the intensive work? Everyday, participants will receive the following in their inbox:
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📚 Daily Assignments
This includes newly published white papers, a companion podcast (generated by NotebookLM), and companion code labs in AI Studio. -
💬 Discord Discussion Threads
Kaggle’s Discord server will have a dedicated channel for focused discussion on the reading. It's an excellent place to find further clarification, surface any questions, and connect with other learners. -
🎥 Daily Livestream Seminars and AMAs
We're going live everyday on Kaggle's YouTube channel, where the authors and course contributors will dive deeper into the topics and answer your burning questions. Plus, we've got fun surprises in store to keep the learning engaging.
What's being covered?
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Day 1:
Foundational Models & Prompt Engineering - Explore the evolution of LLMs, from transformers to techniques like fine-tuning and inference acceleration. Get trained with the art of prompt engineering for optimal LLM interaction. -
Day 2:
Embeddings and Vector Stores/Databases - Learn about the conceptual underpinning of embeddings and vector databases, including embedding methods, vector search algorithms, and real-world applications with LLMs, as well as their tradeoffs. -
Day 3:
Generative AI Agents - Learn to build sophisticated AI agents by understanding their core components and the iterative development process. -
Day 4:
Domain-Specific LLMs - Delve into the creation and application of specialized LLMs like SecLM and Med-PaLM, with insights from the researchers who built them. -
Day 5:
MLOps for Generative AI - Discover how to adapt MLOps practices for Generative AI and leverage Vertex AI's tools for foundation models and generative AI applications.