Building LLM-Powered Apps Course

Learn to build LLM-powered applications using LLM APIs, LangChain, and W&B Prompts through this comprehensive 2 hour 43 minute course from Weights & Biases. Master the entire development lifecycle from initial design and experimentation to evaluation of LLM-based applications. Explore foundational concepts including tokenization, training processes, and sampling methods while gaining hands-on experience with Jupyter notebooks and OpenAI API. Develop expertise in prompt engineering techniques ranging from basic to advanced Level 5 prompts for GPT-4, and discover how to integrate embeddings and vector databases into your applications. Build practical skills in document parsing, QA chain implementation, and web chatbot development while learning to evaluate and enhance LLM application performance. Examine critical topics including AI security essentials, LLM safety considerations, prompt injection vulnerabilities, and output control mechanisms to ensure robust and secure applications.

Syllabus

Kickstart Your Journey in LLM-Powered App Development: Chapter 1
Your Guide to Discord's GPT-4 Wandbot: Chapter 2
Navigating W&B Prompts Tracer for LLMs - Deep Dive into Analysis & Tracking: Chapter 3
LLM Foundations: Understanding Tokenization & Training: Chapter 4
Hands-On LLM Experiments with Jupyter & OpenAI API: Chapter 5
Sampling Methods in LLMs Explained: Chapter 6
Deep Dive into LLM Sampling Techniques: Chapter 7
Mastering OpenAI Chat API in LLM Applications: Chapter 8
Mastering Prompt Engineering for LLMs: Chapter 9
Advancing Prompt Engineering Techniques in LLMs: Chapter 10
Crafting Complex Level 5 Prompts for GPT-4: Chapter 11
Data Analysis & Refinement in LLMs: Chapter 12
Advanced Architectures for LLM Apps - Integrating Embeddings: Chapter 14
Mastering Embedding Stores & Vector Databases in LLM Apps with Anton Troynikov: Chapter 15
Deep Dive into Document Parsing Mastery: Chapter 16
Implementing LLM QA Chains: Chapter 17
LLM Chat Interface & Document Ingestion: Chapter 18
Building Web Chatbots with LLM: Chapter 19
Advanced LLM App Evaluation: Chapter 20
LLM App Enhancement Strategies: Chapter 21
Advanced LLM Evaluation Techniques: Chapter 22
LLM Result Analysis Explained: Chapter 23
Controlling LLM Outputs with Shreya Rajpal: Chapter 24
Unlock AI Security Essentials: Chapter 25
Mastering Blockchain Integration: Chapter 26
Final LLM Course Insights: Chapter 27
Controlling LLM outputs for practical applications
LLM Safety and LLM Prompt Injection
Comprehensive overview of Vector Databases