AI/ML & GenAI Professional Advanced
This 8-week weekend intensive is designed to take participants from AI/ML fundamentals through to building, securing, and deploying production-grade Agentic AI systems. Each session follows a structured 2-hour format: the first hour focuses on theory, architecture, and concepts, while the second hour is dedicated to guided hands-on lab work. Topics build on each other deliberately — foundational ML and GenAI knowledge in Weeks 1–2 unlocks the document processing and RAG work in Week 3, which in turn powers the Agentic AI systems built in Week 4. Developer tooling, DevSecOps, and observability in Weeks 5–7 prepare participants for the capstone in Week 8.
Session Format
Every Saturday and Sunday session follows the same rhythm to maximize learning retention:
- Hour 1 — Theory & Concepts: Lecture, architecture deep-dive, whiteboard discussion, and Q&A. Participants will understand the ‘why’ before the ‘how.’
- Hour 2 — Hands-On Lab: Guided coding exercises, real API integrations, and deployments using the exact tools used in industry. Every lab produces a working artifact participants can keep.
What you'll learn
- Week 1 — AI/ML Foundations & GenAI Landscape
- Week 2 — LLMs Deep Dive — Architecture, Training & Use Cases
- Week 3 — Document Processing Pipelines — RAG & Vector Databases
- Week 4 — Agentic AI — MCP, A2A & Multi-Agent Systems
- Week 5 — AI-Powered Coding Tools & Developer Productivity
- Week 6 — GenAI DevSecOps — Containers, Kubernetes & Production
- Week 7 — GenAI Security, Governance & Observability
- Week 8 — Capstone — End-to-End Agentic AI Project
Technology Stack Covered
- Models & APIs: GPT-5, Claude 4 (Opus/Sonnet/Haiku), Gemini 3, Llama 3, Amazon Bedrock, HuggingFace
- Frameworks: LangChain, LangGraph, AutoGen, LlamaIndex, HuggingFace Transformers, Guardrails AI
- Vector Databases: Pinecone, Weaviate, Chroma, pgvector
Developer Tools: VSCode, GitHub Copilot, Cursor, Claude Code, OpenAI Codex, Kiro, Antigravity - Infrastructure: Docker, Kubernetes (minikube + cloud), GitHub Actions, Helm
- Observability: OpenTelemetry (OTel), Phoenix by Arize.ai, Server-Sent Events (SSE)
Assessment & Certification
Weekly lab deliverables are submitted to a shared GitHub organization for peer and instructor review. Assessment is based on three pillars:
- Lab completion and code quality (50%) — weekly labs reviewed against a provided rubric
- Participation and peer review (20%) — constructive feedback given to at least two peers per week
- Capstone project (30%) — Week 8 end-to-end system evaluated on functionality, security, observability, and deployment quality
Participants who complete all 8 weeks and achieve a passing score on the capstone will receive a digital Certificate of Completion in Advanced GenAI & Agentic AI Engineering.
Prerequisites
- Intermediate Python programming (functions, classes, async/await)
- Basic familiarity with REST APIs and JSON
- Git and command-line proficiency
- Access to OpenAI, Anthropic, and Google AI API keys (free tiers acceptable for Weeks 1–3)
- Docker Desktop installed; cloud Kubernetes account recommended for Week 6
Contact Us for any support during this process and we will be happy to help!
- Email us at info@ideanirvana.com
- Call us at +1 703-606-2049 or +1 703-606-2059
