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In this course, you will :
- Learn how to use LangChain.
- Have a fully functional LangChain-based generative AI application.
- Prompt Engineering Theory: Chain of Thought, ReAct, Few Shot Prompting, and grasp how LangChain is built underneath the hood.
- Learn how to traverse the LangChain opensource codebase.
- Theory of Large Language Models for software developers.
- LangChain: A large number of chains, including Agents, DocumentLoaders, TextSplitters, OutputParsers, and Memory.
- Vectorestores and vector databases (Pinecone, FAISS).
Syllabus :
1. The GIST of LangChain- Get started by with your "Hello World" chain
- Project Setup (Pycharm) recommend)
- Project Setup (vscode) - optional
- Your First LangChain application - Chaining a simple prompt
- Quick Check In
2. Ice Breaker Real World Generative AI application
- Ice Breaker- What are we building here?
- Integrating Linkedin Data Processing - Part 1 - Scraping
- Linkedin Data Processing - Part 2 - Agents Theory
- Linkedin Data Processing- Part 3: Tools, AgentType & initialize_agent
- Linkedin Data Processing- Part 4: Custom Agent Implementation & Testing
- Twitter Data Processing- Part 1- Scraping
- Twitter Data Processing- Part 2- Agents
- Output Parsers- Getting Ready to work with a Frontend
- FullsStack App- Building our LLM powered by LangChain FullStack Application
3. The GIST of Embeddings, Vector Databases and, VectorDBQA chain & RetrievalQA
- Theoretical Introduction to embeddings, Vectorstores & VectorDBQA chain
- LangChain classes review: Pinecone, OpenAIEmbeddings, VectorDBQA, TextLoader
- Medium Analyzer- Boilerplate Project Setup
- Medium Analyzer- Implementation
- Chat With Your PDF- FAISS Local Vectorstore
4. Building a documentation assistant (Embeddings, VectorDBs, RetrievalQA, Memory)
- What are we building?
- Building an AI LangChain Chat Assistant- Vectorstore Pincone Ingestion
- Building an AI LangChain Chat Assistant- RetrievalQA chain (prompt augmentation)
- Building an AI LangChain Chat Assistant- "Frontend" with Streamlit (UI)
- Building an AI LangChain Chat Assistant- Memory & ConversationalRetrievalChain
5. LangChain Theory
- LangChain Token Limitation Handeling Strategies
- LangChain Memory Deepdive
6. Prompt Engineering Theory
- The GIST of LLMs
- What is a Prompt? Composition of a formal prompt
- Zero Shot Prompting
- Few Shot Prompting
- Chain of Thought Prompting
- ReAct
- Prompt Engineering Quick Tips
7. Troubleshooting Section
- Have a technical issue? WATCH THIS FIRST. I Promise this will help ?
- Tweet API- tweepy.errors.Forbidden: 403 Forbidden
