Generative AI for Business Automation

The Evolution of Large Language Models

• From RNNs to Transformers: A Technical Shift 45min
• The Attention Mechanism Explained 💻 60min
• LLM Architectures: Encoder-only vs Decoder-only 30min

Setting Up the AI Development Environment

• Python for AI: Libraries and Virtual Environments 💻 40min
• Managing API Keys and Environment Variables 💻 20min
• Introduction to HuggingFace and OpenAI SDKs 💻 50min

Core Prompting Techniques

• Zero-shot and Few-shot Learning Patterns 🔒
• Chain-of-Thought (CoT) Reasoning 🔒
• System Prompts vs. User Instructions 🔒

Programmatic Prompting

• Dynamic Prompt Templates with Jinja2 🔒
• Output Parsing: Forcing JSON and Structured Data 🔒
• Introduction to DSPy for Programmatic Optimization 🔒

Vector Databases and Embeddings

• Understanding Text Embeddings and Similarity 🔒
• Vector DB Deep Dive: Pinecone and ChromaDB 🔒
• Indexing Strategies for High-Speed Retrieval 🔒

Data Ingestion Pipelines

• Document Loading: PDF, CSV, and SQL 🔒
• Text Chunking Strategies: Recursive vs Semantic 🔒
• Metadata Filtering for Contextual Accuracy 🔒

RAG Evaluation and Optimization

• The RAGas Framework for Evaluation 🔒
• Handling Hallucinations in RAG Pipelines 🔒
• Re-ranking and Hybrid Search Techniques 🔒

Agentic Frameworks

• LangChain: Chains, Memory, and Tools 🔒
• Building Multi-Agent Systems with CrewAI 🔒
• State Management in LangGraph 🔒

Tool Use and Function Calling

• OpenAI Function Calling Deep Dive 🔒
• Connecting LLMs to External APIs 🔒
• Error Handling and Retries in Agentic Flows 🔒

Model Fine-Tuning vs. RAG

• When to Fine-tune: Use Case Analysis 🔒
• Parameter-Efficient Fine-Tuning (LoRA/QLoRA) 🔒
• Preparing Datasets for Instruction Tuning 🔒

Security, Ethics, and Compliance

• Prompt Injection and Jailbreaking Defense 🔒
• Data Privacy: PII Masking and Anonymization 🔒
• Cost Monitoring and Token Optimization 🔒

Project Scoping and Architecture

• Defining the Business Problem and KPI 🔒
• Designing the System Architecture Diagram 🔒
• Selecting the Tech Stack (LLM, DB, UI) 🔒

Development and Deployment

• Building the Backend RAG/Agent Logic 🔒
• Creating a Streamlit/Gradio Frontend 🔒
• Final Testing, Evaluation, and Presentation 🔒