96425 - Large Language Models for Everyone

Course Overview

Large language models course is designed for anyone interested in getting started with large language models and generative AI without all the math and programming.

Understand how machines see and read. Intuitive understanding of the foundations of machine learning, AI and generative AI. An introduction to how images, text, audio and video are converted into vectors. Understanding how embeddings are stored, optimized and retrieved using vector databases.

Understand how generative AI and large language models work. An intuitive overview minus all the math and programming.

Understanding prompt engineering and the role prompt engineering plays in getting the most out of large language models. RAG is one of the most popular paradigms for LLM applications.

Understand the rationale for RAG, how it is implemented and why it is so popular. Understand fine tuning and how it is different from RAG. Discuss when RAG or fine tuning may be the right choice for building LLM applications.

Discuss the risks and challenges in adoption of large language models for enterprise. Learn about RLHF, prompt hacking/jailbreaking, guardrails, AI and data governance. Overview of a canonical enterprise LLM application architecture and all the moving parts.

What You'll Learn

• Fundamentals: Understand how machines see and read. Intuitive understanding of the foundations of machine learning, AI and generative AI.
• Embeddings: An introduction to how images, text, audio and video are converted into vectors.
• Vector Databases: Understanding how embeddings are stored, optimized and retrieved using vector databases.
• Mechanics of Generative AI: Understand how generative AI and large language models work. An intuitive overview minus all the math and programming.
• Prompt Engineering: Understanding prompt engineering and the role prompt engineering plays in getting the most out of large language models.
• Retrieval-Augmented Generation: RAG is one of the most popular paradigms for LLM applications. Understand the rationale for RAG, how it is implemented and why it is so popular.
• Fine-Tuning: Understand fine tuning and how it is different from RAG. Discuss when RAG or fine tuning may be the right choice for building LLM applications.
• Risks and Challenges: Discuss the risks and challenges in adoption of large language models for enterprise. Learn about RLHF, prompt hacking/jailbreaking, guardrails, AI and data governance.
• Enterprise Architectures: Overview of a canonical enterprise LLM application architecture and all the moving parts.

Who Should Attend

Large language models course is designed for anyone interested in getting started with large language models and generative AI without all the math and programming.

Product managers and leaders, startup founders, software developers, consultants, legal professionals, doctors, journalists, compliance officers, business executives are encouraged to attend.

Additional Information

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