00:00:00 – 01. Day 1 – Cold Open Jumping Right into LLM Engineering

00:00:37 – 02. Day 1 – Setting Up Ollama for Local LLM Deployment on Windows and Mac

00:04:52 – 03. Day 1 – Unleashing the Power of Local LLMs Build Spanish Tutor Using Ollama

00:09:00 – 04. Day 1 – LLM Engineering Roadmap From Beginner to Master in 8 Weeks

00:14:45 – 05. Day 1 – Building LLM Applications Chatbots, RAG, and Agentic AI Projects

00:16:35 – 06. Day 1 – From Wall Street to AI Ed Donner s Path to Becoming an LLM Engineer

00:18:42 – 07. Day 1 – Setting Up Your LLM Development Environment Tools and Best Practices

00:24:54 – 08. Day 1 – Mac Setup Guide Jupyter Lab and Conda for LLM Projects

00:31:49 – 09. Day 1 – Setting Up Anaconda for LLM Engineering Windows Installation Guide

00:43:27 – 10. Day 1 – Alternative Python Setup for LLM Projects Virtualenv vs. Anaconda Guide

00:50:00 – 11. Day 1- Setting Up OpenAI API for LLM Development Keys, Pricing & Best Practices

00:57:14 – 12. Day 1 – Creating a .env File for Storing API Keys Safely

01:02:14 – 13. Day 1- Instant Gratification Project Creating an AI-Powered Web Page Summarizer

01:11:46 – 14. Day 1 – Implementing Text Summarization Using OpenAI s GPT-4 and Beautiful Soup

01:25:22 – 15. Day 1 – Wrapping Up Day 1 Key Takeaways and Next Steps in LLM Engineering

01:28:11 – 16. Day 2 – Mastering LLM Engineering Key Skills and Tools for AI Development

01:35:04 – 17. Day 2 – Understanding Frontier Models GPT, Claude, and Open Source LLMs

01:42:47 – 18. Day 2 – How to Use Ollama for Local LLM Inference Python Tutorial with Jupyter

01:49:42 – 19. Day 2 – Hands-On LLM Task Comparing OpenAI and Ollama for Text Summarization

01:50:19 – 20. Day 3 – Frontier AI Models Comparing GPT-4, Claude, Gemini, and LLAMA

01:57:57 – 21. Day 3 – Comparing Leading LLMs Strengths and Business Applications

01:59:47 – 22. Day 3 – Exploring GPT-4o vs O1 Preview Key Differences in Performance

02:03:41 – 23. Day 3 – Creativity and Coding Leveraging GPT-4o s Canvas Feature

02:10:13 – 24. Day 3 – Claude 3.5 s Alignment and Artifact Creation A Deep Dive

02:15:39 – 25. Day 3 – AI Model Comparison Gemini vs Cohere for Whimsical and Analytical Tasks

02:20:26 – 26. Day 3 – Evaluating Meta AI and Perplexity Nuances of Model Outputs

02:25:02 – 27. Day 3 – LLM Leadership Challenge Evaluating AI Models Through Creative Prompts

02:30:43 – 28. Day 4 – Revealing the Leadership Winner A Fun LLM Challenge

02:38:33 – 29. Day 4 – Exploring the Journey of AI From Early Models to Transformers

02:41:36 – 30. Day 4 – Understanding LLM Parameters From GPT-1 to Trillion-Weight Models

02:46:37 – 31. Day 4 – GPT Tokenization Explained How Large Language Models Process Text Input

02:57:18 – 32. Day 4 – How Context Windows Impact AI Language Models Token Limits Explained

03:00:32 – 33. Day 4 – Navigating AI Model Costs API Pricing vs. Chat Interface Subscriptions

03:03:21 – 34. Day 4 – Comparing LLM Context Windows GPT-4 vs Claude vs Gemini 1.5 Flash

03:08:43 – 35. Day 4 – Wrapping Up Day 4 Key Takeaways and Practical Insights

03:11:24 – 36. Day 5 – Building AI-Powered Marketing Brochures with OpenAI API and Python

03:14:32 – 37. Day 5 – JupyterLab Tutorial Web Scraping for AI-Powered Company Brochures

03:20:53 – 38. Day 5 – Structured Outputs in LLMs Optimizing JSON Responses for AI Projects

03:30:13 – 39. Day 5 – Creating and Formatting Responses for Brochure Content

03:38:52 – 40. Day 5 – Final Adjustments Optimizing Markdown and Streaming in JupyterLab

03:48:43 – 41. Day 5 – Mastering Multi-Shot Prompting Enhancing LLM Reliability in AI Projects

03:53:05 – 42. Day 5 – Assignment Developing Your Customized LLM-Based Tutor

03:57:12 – 43. Day 5 – Wrapping Up Week 1 Achievements and Next Steps