Advanced certification in Gen AI & Agentic AI for Working Professionals
From Python developer to GenAI Agent Engineer — build LLM apps, RAG systems, and multi-agent products in an intensive career sprint.
What this program is about
A career-focused, project-based program that takes professionals from ML fundamentals to production-ready GenAI Agent Engineers. Build LLM applications, RAG systems, and multi-agent products using the same stack modern AI teams use — OpenAI, Anthropic, LangChain, LangGraph, CrewAI, FastAPI, and more.
Who it's for
- Software engineers moving into Advanced certification in Gen AI & Agentic AI and GenAI roles
- Data analysts levelling up into ML and LLM development
- Backend & full-stack engineers building AI features
- Managers, consultants and non-tech professionals leading AI initiatives
What you'll learn
Curriculum
Phase 0 · ML & Deep Learning Foundations (Weeks 1–2)
- Applied Machine Learning refresh
- Supervised & Unsupervised learning
- Neural networks & backpropagation
- Transformers, BERT vs GPT
- Hugging Face pipelines
- Project: Sentiment Analysis Classifier
Phase 1 · GenAI & Prompt Engineering (Weeks 3–4)
- How LLMs work
- OpenAI & Anthropic APIs
- Prompt engineering, few-shot & Chain of Thought
- JSON outputs & function calling
- Pydantic for structured outputs
- Local models with Ollama
- Projects: CLI Chatbot, Resume Analyzer
Phase 2 · RAG — Retrieval Augmented Generation (Weeks 5–6)
- Embeddings & vector databases
- ChromaDB, Pinecone & Qdrant
- Semantic search, chunking & hybrid search
- FastAPI for RAG APIs
- Projects: Semantic PDF Search, Company Knowledge Base Chatbot
Phase 3 · AI Agents & Multi-Agent Systems (Weeks 7–9)
- Function calling & custom tools
- ReAct agents
- LangChain & LangGraph
- CrewAI & multi-agent systems
- Supervisor + Worker agent patterns
- Projects: Research Agent, Job Application Assistant, Planner + Coder + Critic
Phase 4 · Memory & Observability (Week 10)
- Short-term & long-term memory
- Redis & PostgreSQL for agent state
- LangSmith & LangFuse for tracing
- Prompt caching & cost control
Phase 5 · Deployment & Career Sprint (Weeks 11–12)
- FastAPI & Streamlit
- Docker & containerized deployment
- MCP (Model Context Protocol)
- Slack & GitHub integrations
- Resume review, LinkedIn optimization
- Mock interviews, portfolio & demo video
Industry use cases
- Automating repetitive knowledge work with agents
- Building internal AI copilots and assistants
- Enterprise document intelligence with RAG
- AI-driven analytics and reporting
- Customer support automation
- Multi-agent research & operations workflows
Live practical sessions
Weekend live practical sessions with industry mentors — recorded, hands-on, and focused on real workplace scenarios.
Portfolio projects
- Sentiment Analysis Classifier (Hugging Face)
- CLI Chatbot with OpenAI & Anthropic
- Resume Analyzer with structured outputs
- Semantic PDF Search Engine
- Company Knowledge Base RAG Chatbot
- Research Agent with tools
- Job Application Assistant
- Planner + Coder + Critic Multi-Agent System
- Capstone: Deployed GenAI Agent product
Tools you'll use
Career outcomes
- AI Engineer
- LLM Application Developer
- GenAI Platform Engineer
- AI Automation Engineer
- AI Product Manager
- AI Solutions Lead
Career transition guidance
One-on-one career strategy, resume rewrite for AI roles, LinkedIn optimization, mock technical interviews, portfolio and demo video coaching, and referral guidance to help you transition confidently into GenAI roles.
Certificate of completion
Earn a GeekX United Certificate of Completion — backed by a full applied AI portfolio including a deployed capstone agent product.