1 Skills & Project requirements (20 MB)
2 Development Environment Setup (28.43 MB)
3 1 starter-project (4.02 KB)
4 Integrate OpenAI into a Web Project (Quickstart) (41.75 MB)
5 Integrate OpenAI into a Web Project (Quickstart) send first API request (44.68 MB)
5 1 final (4.04 KB)
1 Introduction (22.99 MB)
11 Build an End-2-End RAG Pipeline (ChromaDB) - Part 2 (70.92 MB)
11 1 final (4.04 KB)
13 Interactive playground (Google Colab) With or Without RAG (79.15 MB)
15 Advanced Techniques to Enhance the RAG pipeline (13.78 MB)
16 1 course-materials (51.39 KB)
17 [Part 14]-Advanced RAG Query Translation and Enhancement (Decomposition) (71.92 MB)
18 [Part 24]-Advanced RAG Query Decomposition and Enhancement - Answer queries (80.32 MB)
19 [Part 34] - Advanced RAG Query Decomposition and Enhancement - Optimized Answ (28.32 MB)
20 [Part 44]-Advanced RAG Query Decomposition and Enhancement (45.76 MB)
3 Starter project Installation & Setup (56.15 MB)
3 1 starter-project (5.44 KB)
4 Retrieval QA Integration (FAISS) (63.98 MB)
6 Retrieval QA integration Retriever and Generate components (66.2 MB)
6 1 final (4.04 KB)
8 The Main Building Blocks (13.82 MB)
9 Build an End-2-End RAG Pipeline (ChromaDB) (84.31 MB)
9 1 starter-project (4.02 KB)
1 Introduction (12.99 MB)
10 [Part 14] - Advanced RAG Corrective RAG (62.4 MB)
11 [Part 24] - Advanced RAG Corrective RAG - Retrieval Evaluator (67.53 MB)
12 [Part 34] - Advanced RAG Corrective RAG - Rewrite & web tool (63.91 MB)
13 [Part 44] - Advanced RAG Corrective RAG - generate response (98.79 MB)
13 1 final (7.56 KB)
3 1 starter-project (7.16 KB)
4 [Part 12] - Advanced RAG multi-querying, retrieve and consolidate results (60.21 MB)
4 1 final (5.84 KB)
5 [Part 22] - Advanced RAG multi-querying and generate accurate answers (36.02 MB)
5 1 final (5.89 KB)
6 1 starter-project (7.9 KB)
7 [Part 12] - Advanced RAG Fusion - multi-querying and reranking results (33.4 MB)
7 1 final (7.8 KB)
8 [Part 22] - Advanced RAG Fusion - generate context-aware responses (33.59 MB)
8 1 final (7.17 KB)
9 1 starter-project (8.6 KB)
1 Section intro Smart Text Division with LangChain (28.87 MB)
10 Levels 4 & 5- Semantic Chunking (Embeddings-based) & Agentic approach (66.95 MB)
10 1 course-materials (21.34 KB)
2 Level 1 - Split documents by Character vs Recursively (62.95 MB)
2 1 course-materials (22.86 KB)
4 Level 2 - Split documents by character vs recursively (40.58 MB)
4 1 course-materials (19.91 KB)
5 Levels 3 - Document specific splitting split code and markup (45.56 MB)
5 1 final (21.68 KB)
5 2 starter-project (22.19 KB)
6 Levels 3 - Document-specific splitting Code Splitting (Python) (76.63 MB)
6 1 final (22.27 KB)
6 2 starter-project (23.14 KB)
7 Levels 3 - Document-specific splitting PDF (unstructured io) (76.56 MB)
7 1 starter-project (501.96 KB)
8 Levels 3 - Document-specific splitting extract and process elements from PDF d (43.11 MB)
8 1 final (404.36 KB)
1 Introduction (16.44 MB)
2 RAG Implementation Tracing & Testing (88.21 MB)
2 1 course-materials (21.27 KB)
3 Integrating LangSmith into your workflow (35.51 MB)
3 1 course-materials (6.15 KB)
1 Introduction (19.74 MB)
2 Getting Started Agent-based Workflow with LangGraph (57.39 MB)
2 1 starter-project (8.73 KB)
3 Getting Started Compile and Run the App (with Streamlit) (51.23 MB)
3 1 final (8.5 KB)
4 1 starter-project (9.92 KB)
5 Define the Nodes (78.92 MB)
6 Define the Edges (18.87 MB)
7 Build the Workflow with Langraph (20.93 MB)
8 Compile and Run the Workflow (68.54 MB)
8 1 final (10.65 KB)
1 INTRO - Semi-structured RAG to manage multiple data sources and content (16.77 MB)
2 Extract elements from PDF tables, images (43.6 MB)
2 1 starter-project (9.92 KB)
3 Describe images with GPT-4 Vision (60.8 MB)
4 Process data sources into documents, index, retrieve and generate with LLM (12.8 MB)
4 1 final (10.65 KB)