Modren AI: llms

Module 1

Introduction to Modern LLMs Architecture

Explore the underlying architecture of modern Large Language Models, focusing on the evolution of transformers and the mechanisms that enable sophisticated natural language understanding.

Module 2

Pre-training and Fine-tuning Strategies

Understand the lifecycle of LLM training, from massive-scale pre-training paradigms to efficient fine-tuning techniques tailored for specific downstream tasks.

Module 3

Reinforcement Learning from Human Feedback (RLHF)

Delve into the alignment phase of modern LLMs, learning how human preferences and reinforcement learning are used to make models safer and more helpful.

Module 4

Retrieval-Augmented Generation (RAG)

Learn how to overcome LLM hallucinations and data staleness by grounding generative models with external knowledge bases using RAG architectures.

Module 5

Prompt Engineering and LLM Agents

Transition from basic prompting to complex orchestrations, teaching LLMs to reason, use external tools, and operate as autonomous agents.

Module 6

Deployment, Optimization, and Ethics

Discover the practical challenges of deploying LLMs in production, covering inference optimization, model quantization, and crucial ethical considerations.

Module 7

Final Assessment

A comprehensive evaluation covering all concepts taught in the Modern AI: LLMs course to ensure mastery of intermediate-level topics.