Home
1.
Introduction
FAQ
Modules & Lessons details
2.
Development
Setup instructions
Coding exercises
Running sample code
Intro to Jupyter
Intro to Anaconda
Intro to Google Colab
Try out : Groq API Key
FAQ
3.
Fundamentals of AI-ML
ML Functions
Natural Language Processing
Exercise#1 Neural Network
4.
Fundamentals of Gen AI
Decoding hyperparameters
LLM challenges
Exercise#1 Setup key file
Exercise#2 Google API Key
Exercise#3 HuggingFace Token
Exercise#4 Explore NLP Tasks
Exercise#5 Cohere account
Exercise#6 Decoding Parameters
5.
Hugging Face
Model & Config classes
Tokenizer classes
Ex: Install Transformers
Ex: Install hub library
Ex: Model HTTP Invoke
Exercise#1 Summarization PoC
Exercise#2 Question-Answering
Exercise#3 Table Q&A
FAQ
6.
Datasets
Exercise#1 Datasets library
Exercise#2 Create & publish dataset
7.
LangChain
Prompt templates
LLM
Chains : LCEL
Output Parsers
Loaders & Splitters
Chatbots
Retrievers
RAG
Agents
Tools
Evaluations
Exercise#1 LLM & Fakes
Exercise#2 Create LLM Utility
Exercise#3 Sequential chain
Exercise#4 LCEL Cheatsheet & Howtos
8.
Prompt Engineering
Best Practices
Few Shot
Chain of Thought
Self Consistency
Tree of Thought
Model specificity
Exercise#1 Fix prompts
Exercise#2 Few Shot
Exercise#2 Few Shot : Code
Exercise#3 CoT
Exercise#4 ToT Prompt
Exercise#5 ToT-v1
Exercise#6 ToT-v2
Exercise#7 Fix the prompt
9.
Structured Data
Exercise#1 Enumerations Parser
Exercise#2 Pydantic Parser
Project: Creative writing workbench (v3)
10.
Embeddings
Encoder models
SBERT
Algorithms
FAISS
Benchmarking
Curse of dimensionality
Exercise# FAISS Indexing
Exercise#1 Classification & mining
Exercise#2 CacheBackedEmbedding class
Exercise#3 Benchmarking ANN
Project: Movie Recommendation
11.
Streamlit
Exercise#1 HF LLM Playground
Exercise#2 Chatbot
Exercise#3 LangChain memory
Project : PDF Summarizer
12.
Vector Databases
Exercise#1 Try out ChromaDB
Project# Pinecone VectorStore
13.
RAG
Exercise#1 Retrieval History
Exercise#2 Multi Query Retriever
Exercise#3 Parent Documents Retriever
Exercise#4 Ensemble Retriever
Exercise#5 Multi Vector Retriever
Exercise#6 Large Context Reorder
Exercise#7 Contextual Compressor
Exercise#8 Merger Retriever
14.
Agentic RAG
30.
ReAct
Exercise#1 Single step agent
Exercise#2 File Tool
Exercise#3 Multi step agent
Exercise#4 Create agent functions
15.
Fine tuning
Exercise#1 Domain adapted models
16.
Inference endpoints
Ollama
Companion guide course on
DynamoDB Data Modeling
Gen AI Guide
> Fine tuning
Fine tuning
References
Domain adaptation models & datasets