Module 1: Introduction to Generative AI
- Overview of Generative AI
- Generative AI vs. Traditional AI
- Use Cases
- Understanding AI: Basics and Use Cases
- Differentiating ML, DL and AI
- Basics of NLP
Module 2: Large Language Models
- Introduction to OpenAI and LLMs
- What are LLMs?
- How do LLMs work?
- Types of LLMs
- Practical uses of LLM
- Text Generation
- Chatbot Creation
- Foundations of Generative Models & LLM
- Generative Adversarial Networks (GANs)
- Autoencoders in Generative AI
- Significance of Transformers in AI
- Attention is All You Need" - Transformer Architecture
- Reinforcement Learning RLHF
Module 3: LLMs Foundation Models
- Encoder Models i.e.BERT
- Decoder Models GPT
- Encoder Decoder Model i.e.T5
- Open-Source Models vs Commercial Models
- Quantization Models (GGML Vs GGUF)
Module 4: LangChain & Lama Index Framework
- Introduction to LangChain & Lamaindex
- Hugging Face API + Langchain
- Hugging Face API + Lamaindex
- Memory in Langchain
- LLM Chain
Module 5: Retrieval Augmented Generation (RAG) And Evaluating RAG
- Overview of RAG
- Intro to Semantic Search, Vectors and Vector Databases
- How to build a Gen AI app with RAG
- Evaluating RAG
- End to End Medical Chatbot Project
Module 7: Fine Tuning and Evaluating LLMs
- Instruction fine-tuning
- Fine-tuning on a single task
- Multi-task instruction fine-tuning
- Model evaluation
- Benchmarks
- Parameter efficient fine-tuning (PEFT)
- PEFT techniques 1: LoRA
- PEFT techniques 2: Soft prompts
- Lab 2 walkthrough
Module 8: Evaluation Matrix
Module 9: Deployment And Hardware Considerations
- Deployment Strategies
- Hardware Requirements
Module 10: Introduction To Generative AI On Cloud: Hugging Face / Hugging Face Hub
- Hugging Face
- Hugging Face Overview
Module 11: Generative AI On Cloud - GCP
- Model Evaluation
- Prompt Design
Module 12: Generative AI On Cloud - Azure
- Azure ML
- Azure Cognitive Services
- Azure Databricks
Module 13: Generative AI On Cloud - AWS
Module 14: Introduction To ChatGPT & Architectures
- Introduction to GPT and ChatGPT
- Overview of GPT
- ChatGPT Capabilities
- GPT Architecture
- Understanding GPT-3, GPT 3.5, and GPT-4
- GPT-3 vs GPT-4
- Advancements in GPT-4
- Ethical Considerations
Module 15: Introduction To Prompt Engineering
- The Fundamentals of Prompt Engineering
- What is prompt engineering
- Its importance
- Types of prompts
- Content Generation with Prompts
- Strategies for generating text
- Video scripts
- Music using prompts
- Tokens and Parameters in AI
- The role and understanding of tokens
- Introduction to prompt parameters
Module 16: Advanced Prompt Techniques
- Zero-Shot to Few-Shot Learning
- Deep dive into zero-shot
- One-shot
- Few-shot learning
- Fine-Tuning AI Model Parameters
- Introduction to model parameter adjustments
- Hallucinations and Bias in AII
- Strategies for managing AI hallucinations and biases
- Advanced Prompt Engineering Techniques
- Methods for crafting complex prompts
- Incorporating creativity and context
- Refining and Optimizing Prompts
- Techniques for prompt refinement and iterative improvement
Module 17: Agents
- Overview of Agents
- LangChain Agents
- AWS Bedrock Agents
- Crew AI
Module 18: Guardrails
- Overview of Guardrails
- Implement Guardrails
- AWS, Azure Guardrails
Module 19: Github Co-Pilot
- Overview of GitHub Co-Pilot
- Practice Copilot with complex coding projects
- Generate, document, explain and test code in a few seconds with effective prompting
- Leverage GitHub Copilot's capabilities to write better code, faster
- Commands
- Agents
Module 20: Generative AI for Software Testing
- Generate Documentation (Test Cases, Artifacts) using Gen AI
- Leveraging AI for understanding Test Scripts
- Generate Test Cases & Test Scripts from an Image
- Developing a QA Strategy with Generative AI
Module 21: Real World Applications and Case Studies
- End to End Gen AI Project using Google Gemini Pro
- Medical Chatbot
- Talk to your codebase
- Code Translation and Conversion
- Chatbot to talk to complex pdf
- Self-healing code
- NLP to SQL
