Advanced Generative AI Professional Program

• What is Generative AI
• Generative models vs discriminative models
• Evolution of generative models
• GANs vs Diffusion vs LLMs
• Key Generative AI applications
• Enterprise use cases

Hands-on:

• Text generation
• Image generation
• AI content creation

• Python basics for AI
• Data structures for AI workflows
• Working with APIs
• JSON and data pipelines
• Data preprocessing for AI
• Working with notebooks

Hands-on:

• Python scripts interacting with AI APIs

• Transformers architecture
• Tokens and tokenization
• Embeddings
• Attention mechanism
• Context window
• Training vs inference
• Hallucination in LLMs
• LLM limitations

LLM ecosystem overview:

• GPT
• Gemini
• Claude
• LLaMA
• Mistral

Hands-on:

• Interacting with LLM APIs

• Role of prompts in LLM behavior
• Prompt design patterns
• Zero-shot prompting
• Few-shot prompting
• Chain-of-thought reasoning
• Prompt templates
• Prompt evaluation

Hands-on:

• Prompt optimization
• Structured prompt design

• Prompt orchestration
• Output formatting
• Function calling
• Tool integration
• Guardrails and safety

Hands-on Projects:

• AI blog generator
• AI document summarizer
• AI research assistant

• What are embeddings
• Semantic similarity
• Vector search
• Indexing techniques

Hands-on Projects:

• Build semantic search system

• RAG architecture
• Document ingestion
• Chunking strategies
• Retrieval pipelines
• Hybrid search
• Re-ranking techniques
• RAG evaluation

Hands-on:

• Build a Document AI Assistant

• Fine tuning vs prompting
• Dataset preparation
• Instruction tuning
• Parameter efficient fine tuning

Methods:

• LoRA
• QLoRA

Hands-on:

• Fine tune model on custom dataset

• AI agents architecture
• Agent planning
• Task execution
• Multi-agent systems

Hands-on Projects:

• Build AI workflow automation agent

• Image generation
• Video generation
• Voice AI
• Multimodal models

Hands-on:

• Build AI media generation workflow

• AI bias and fairness
• Explainable AI
• AI security risks
• Privacy concerns
• Regulatory frameworks

Examples:

• EU AI Act
• Responsible AI frameworks

• AI product lifecycle
• Identifying AI opportunities
• AI ROI and cost optimization
• AI transformation strategy

Case studies:

• AI copilots
• AI knowledge assistants
• AI automation systems

Students build a complete Generative AI system.

Example capstone options:

• AI Customer Support Copilot
• AI Research Assistant
• AI Knowledge Base System
• AI Resume Analyzer
• AI Document Intelligence Platform

Final evaluation:

• System architecture
• Model performance
• Business relevance
• Presentation