Python Generative AI & Agentic AI
FlagshipEnd-to-end applied learning from Python programming to advanced Generative AI, LLMs, and production-grade Agentic AI deployment.
🎯 Duration
3 Months
💰 Fee
₹40,000
👥 Audience
Students, Professionals, Researchers
🎓 Certificate
Certified Applied Agentic AI Engineer, AI Engineer, AI/ML Engineer, AI Architect
Phase 1: Python Foundations (Zero to Pro)
- Module 1: Introduction to Programming with Python
- Module 2: Python Data Types, Functions and Control Structures
- Module 3: Object-Oriented Programming and Modular Design
- Module 4: Working with Files, JSON and CSV
- Module 5: Python for APIs, Webhooks and Data Exchange
- Module 6: Async Programming and Concurrency in Python
- Module 7: Building and Testing APIs with FastAPI and Flask
- Module 8: Working with Databases
- Module 9: Logging, Debugging and Exception Handling
- Module 10: Packaging, Virtual Environments and Docker Basics
- Module 11: Git, GitHub and Project Workflow for AI Development
- Module 12: REST API and Async Data Service
Phase 2: NLP and Generative AI (Foundation to Applied Systems)
- Module 13: Introduction to Natural Language Processing
- Module 14: Text Preprocessing, Cleaning and Tokenization
- Module 15: Word Embeddings and Semantic Understanding
- Module 16: Vector Databases and Search Systems
- Module 17: Transformer Architecture and LLM Fundamentals
- Module 18: Attention Mechanism and Decoder Models
- Module 19: Fine-Tuning and Adaptation (LoRA, PEFT, SFT)
- Module 20: Quantization and Optimization Techniques
- Module 21: Prompt Engineering and Structured Prompt Design
- Module 22: Retrieval-Augmented Generation (RAG) Architecture
- Module 23: Cloud SDKs and AI Service Integration
- Module 24: Generative AI for Text, Code and Image Applications
- Module 25: Evaluation, Metrics and Hallucination Testing
- Module 26: Build Your Own Document Q&A RAG Chatbot
Phase 3: Agentic AI Systems
- Module 27: Introduction to AI Agents and Autonomy Concepts
- Module 28: Coding Fundamentals for Agent Systems
- Module 29: LangChain Fundamentals — Chains, Tools and Memory
- Module 30: Building AI Agents from Scratch
- Module 31: LangGraph and Workflow-Oriented Agent Design
- Module 32: CrewAI for Multi-Agent Team Collaboration
- Module 33: AutoGen for Cooperative Agents
- Module 34: Building AI Agents for Real-World Use Cases
- Module 35: Agentic RAG Systems with LangGraph and AutoGen
- Module 36: Domain-Specific Agents
- Module 37: Offline and Edge Agent Deployment
- Module 38: Advanced Multi-Agent Architectures
- Module 39: Responsible, Safe and Governed Agent Design
- Module 40: Project — Multi-Agent AI Workflow System
Phase 4: MLOps and LLMOps (Deployment to Production)
- Module 41: MLOps Fundamentals and Version Control
- Module 42: MLflow for Experiment Tracking and Model Registry
- Module 43: CI/CD for AI Projects
- Module 44: Containerization and Orchestration (Docker, Kubernetes)
- Module 45: LLMOps — Serving, Monitoring and Scaling Models
- Module 46: Offline LLM Hosting and Quantized Deployments (vLLM)
- Module 47: Monitoring and Observability
- Module 48: Security and Compliance for AI Systems
- Module 49: Responsible AI and Ethical Governance
- Module 50: AI Cost Optimization and Resource Planning
- Module 51: Deploy Enterprise-Grade Agentic AI Platform
- Module 52: System Design and AI Product Architecture
- Module 53: AI Governance and Audit System