What is Generative AI & Why It Matters in 2025

Generative AI vs Traditional AI vs Machine Learning

Types of Generative AI — Text, Image, Audio, Video, Code

Real-World Generative AI Use Cases

Generative AI Market — Tools, Platforms & Companies

Generative AI Career Roadmap — Roles & Skills 2025

– Risks & Limitations — Hallucinations, Bias, Security

Responsible AI — Ethics & Governance

Lab: Explore ChatGPT, Claude, Gemini — Prompt Comparison

Python Refresher for AI Engineers

Virtual Environments — venv & conda

Essential Libraries Overview

Working with JSON & Structured Outputs

File Handling — PDF, DOCX, TXT, CSV for AI Pipelines

Python Async — asyncio for AI Applications

Error Handling & Logging in AI Applications

Lab: Build Simple Python Script to Call OpenAI API

Lab: Parse PDF & Text Files for AI Processing

What is a Large Language Model (LLM)

How LLMs Work — Transformers Architecture (Overview)

Tokens — What They Are & Why They Matter

Context Window — Limits & Strategies

LLM Parameters — Temperature, Top-P, Top-K, Max Tokens

LLM Families & Models

Closed Source vs Open Source LLMs — When to Use What

LLM Benchmarks — MMLU, HumanEval, HellaSwag

Multimodal LLMs — Text + Image + Audio

LLM APIs — OpenAI, Anthropic, Google, Hugging Face

Lab: Compare LLM Outputs — GPT-4o vs Claude vs Gemini

Quiz: LLM Fundamentals — 15 Questions

What is Prompt Engineering & Why It Matters

Anatomy of a Good Prompt

Prompting Techniques

Prompt Templates — Reusable Prompt Patterns

Avoiding Hallucinations with Better Prompts

Prompt Injection Attacks & Defense

Prompt Chaining — Connect Multiple Prompts

Output Formatting — JSON, Markdown, Tables

Prompt Versioning & Management

Lab: Prompt Engineering for Data Extraction Task

Lab: Chain of Thought — Complex Reasoning Tasks

Lab: Build Reusable Prompt Template Library

Quiz: Prompt Engineering — 20 Questions

OpenAI API — Complete Guide

Anthropic Claude API

Google Gemini API

Hugging Face Inference API

LLM API Cost Optimization

Rate Limiting & Error Handling — Retry Logic

Lab: Build Multi-Provider LLM Wrapper in Python

Lab: Streaming Chat Application with OpenAI API

What is LangChain & Why Use It

LangChain Architecture — Components Overview

LangChain Models — LLMs & Chat Models

LangChain Prompts

LangChain Chains

LangChain Memory

LangChain Document Loaders

LangChain Text Splitters

LangChain Output Parsers

LangChain Expression Language (LCEL)

LangChain Tools & Toolkits

LangSmith — Tracing & Debugging LangChain Apps

Lab: Build Conversational Chatbot with Memory

Lab: Multi-Step Document Processing Chain

Lab: LangSmith — Debug & Trace LLM Application

Quiz: LangChain — 20 Questions

What is RAG & Why It Solves Hallucination Problem

RAG Architecture — Complete Flow

Embeddings — What They Are & How They Work

Embedding Models Comparison

Vector Databases — Complete Guide

Chunking Strategies — Critical for RAG Quality

Similarity Search — Cosine, Dot Product, Euclidean

RAG Pipeline with LangChain

RAG Pipeline with LlamaIndex

Advanced RAG Techniques

RAG Evaluation — Metrics & Tools

RAG on Structured Data — SQL + LLM

Multimodal RAG — Images + Text

Filter extraneous content in source documents that degrades RAG quality

Lab: Build RAG Chatbot on Your Own PDF Documents

Lab: Advanced RAG with Hybrid Search & Reranking

Lab: Evaluate RAG Pipeline with RAGAs

Quiz: RAG Concepts — 20 Questions

What is LlamaIndex & How It Differs from LangChain

LlamaIndex Core Concepts

Index Types in LlamaIndex

LlamaIndex Data Connectors — 100+ Sources

LlamaIndex Response Synthesizers

LlamaIndex with Databricks

Advanced LlamaIndex

LlamaIndex Evaluation — Faithfulness & Relevancy

LlamaIndex vs LangChain — When to Use What

Lab: Multi-Document Q&A System with LlamaIndex

Lab: Sub-Question Query Engine for Complex Queries

What is Fine-Tuning & When to Use It vs RAG

Fine-Tuning vs RAG vs Prompt Engineering — Decision Guide

Types of Fine-Tuning

Fine-Tuning Dataset Preparation

Fine-Tuning with OpenAI API

Fine-Tuning Open Source Models

Fine-Tuning on Databricks

Model Evaluation — BLEU, ROUGE, Perplexity

Quantization — GPTQ, GGUF, AWQ

Deploying Fine-Tuned Models

Lab: Fine-Tune LLaMA 3 with LoRA on Custom Dataset

Lab: Fine-Tune OpenAI Model on Domain-Specific Data

Quiz: Fine-Tuning — 15 Questions

What is Agentic AI & Why It Is the Future

AI Agent vs Simple LLM Call — Key Difference

Agent Architecture — Complete Overview

ReAct Framework — Reason + Act

Agent Types

Databricks AI — Complete Platform for GenAI

Mosaic AI — Databricks GenAI Stack

Databricks Runtime ML — Optimized for AI

Writing Chunked Text into Delta Lake — Unity Catalog

MLflow PyFunc Chain

Databricks Model Serving

Databricks Foundation Model APIs

Databricks AI Playground — Interactive LLM Testing

Databricks Vector Search — Enterprise RAG

Databricks AI Functions — SQL + LLM

MLflow for GenAI

Build RAG on Databricks

Databricks GenAI Pipeline — End to End

Ingest Documents → Delta Lake – Chunk & Embed → Vector Search – Query → Retrieve → Generate → Serve

Lab: Build RAG with Databricks Vector Search

Lab: Use AI Functions in SQL — Classify & Summarize

Lab: Full GenAI Pipeline on Databricks Lakehouse

Quiz: Databricks GenAI — 20 Questions

RAG Failure Modes — Why RAG Fails in Production

Advanced Chunking

Advanced Retrieval Techniques

Query Transformation

GraphRAG — Microsoft Knowledge Graph + RAG

Corrective RAG (CRAG)

Self-RAG — LLM Decides When to Retrieve

Adaptive RAG — Dynamic Strategy Selection

RAG Caching — Semantic Cache

RAG with Structured Data

Multimodal RAG

Lab: GraphRAG — Build Knowledge Graph from Documents

Lab: Hybrid Search + Reranking Pipeline

Lab: Text-to-SQL Agent with RAG Fallback

Why LLM Evaluation is Critical in Production

Types of Evaluation

RAG Evaluation Metrics

RAGAs Framework — Automated RAG Evaluation

LLM as Judge — Use GPT-4 to Evaluate Outputs

DeepEval — LLM Testing Framework

Promptfoo — Prompt Testing & Comparison

LangSmith — Tracing & Observability

Arize Phoenix — Open Source LLM Observability

MLflow LLM Evaluate — Databricks Integration

A/B Testing Prompts in Production

Inference Tables in Databricks — Track Live LLM Endpoint

Monitoring LLMs in Production

Lab: Evaluate RAG Pipeline with RAGAs

Lab: LangSmith Tracing — Debug Multi-Agent System

Lab: MLflow Evaluate — LLM Quality Metrics on Databricks

Production GenAI Architecture — Best Practices

FastAPI for LLM Applications

Streamlit for GenAI Demos

Gradio for AI Applications

LLM Caching — Reduce Cost & Latency

Async LLM Calls — Handle High Throughput

Token Optimization Strategies

Security for GenAI Applications

Cost Management

Containerize GenAI App — Docker

Legal & licensing requirements for data sources — copyright, fair use, open source licenses

Deploy GenAI App — Cloud Options

Lab: Build Production RAG API with FastAPI

Lab: Streamlit Chat Application with File Upload

Lab: Add Guardrails to LLM Application

Why Run LLMs Locally — Privacy & Cost

Popular Open Source LLMs

Ollama — Run LLMs Locally

LM Studio — GUI for Local LLMs

Hugging Face Transformers — Load & Run Models

GGUF Format — Quantized Models for CPU

vLLM — High Throughput LLM Serving

Llama.cpp — Efficient CPU Inference

Open Source Embeddings — Nomic, BGE, E5

Build Private RAG with Ollama + Chroma

Lab: Run LLaMA 3 Locally with Ollama

Lab: Build Fully Private RAG — No Cloud APIs

GenAI Use Cases in Data Engineering

Text-to-SQL — Natural Language to SQL Queries

Data Pipeline Code Generation

Data Quality with LLMs

Document Processing Pipelines

LLM for Data Catalog

Databricks AI Functions for Data Teams

Lab: Text-to-SQL Agent on Data Warehouse

Lab: Auto-Generate Column Descriptions using LLMs

Lab: Process 1000 PDFs with LLM Pipeline on Databricks

Project 1 — Enterprise RAG Chatbot (Production Grade)

Project 2 — Multi-Agent Data Analysis System

Project 3 — Databricks GenAI Data Pipeline

AWS Certified Machine Learning Specialty — GenAI Topics

Google Cloud Professional ML Engineer — GenAI Topics

Databricks Generative AI Engineer Associate — Full Guide

Microsoft AI-102 Azure AI Engineer — Overview

DeepLearning.AI Courses — Recommended Path

Practice Questions — Full Mock Tests 100 Questions

Top 60 Generative AI Interview Questions & Answers

Resume Building for GenAI Engineer Roles

LinkedIn Profile Optimization

Salary Negotiation — GenAI Engineer Roles