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Advanced certification in Gen AI & Agentic AI · Students
Advanced certification in Gen AI & Agentic AI for Students
Go from Python beginner to AI Engineer — build real ML models, RAG apps, and AI agents with a project-driven curriculum.
16 weeks · ~10 hrs/week Beginner
Overview
What this program is about
A hands-on Advanced certification in Gen AI & Agentic AI program built for students. Starting from Python fundamentals, you'll progress through Machine Learning, Deep Learning, Generative AI, RAG systems, and AI Agents — building a portfolio of 8+ real projects and a deployed capstone product by the end.
Who it's for
- College students in engineering, science, or maths streams
- First-time coders exploring an AI-focused career path
- Learners who want a strong, project-driven foundation
- Students preparing for internships and campus placements
What you'll learn
Python ProgrammingNumPy, Pandas & Data VisualizationStatistics & Math for MLMachine Learning (supervised & unsupervised)Deep Learning & Neural NetworksTransformers & Hugging FaceLLMs & Prompt EngineeringRAG & Vector DatabasesAI Agents with LangChain / LangGraphFastAPI & Streamlit deployment
Curriculum
01
Phase 0 · Python & Data Foundations (Weeks 1–3)
- Python syntax, data types & control flow
- Functions, modules & OOP basics
- NumPy & Pandas for data handling
- Data cleaning & visualization (Matplotlib, Seaborn)
- Git & GitHub workflow
02
Phase 1 · Math & Machine Learning (Weeks 4–6)
- Probability, statistics & linear algebra intuition
- Supervised & Unsupervised learning
- Regression, classification & clustering
- Model evaluation & feature engineering
- Hands-on with scikit-learn
03
Phase 2 · Deep Learning & Transformers (Weeks 7–9)
- Neural networks & backpropagation
- PyTorch basics
- Computer vision starter
- Transformers explained
- BERT vs GPT & Hugging Face pipelines
04
Phase 3 · Generative AI & Prompt Engineering (Weeks 10–11)
- How LLMs work end-to-end
- OpenAI & Anthropic APIs
- Prompt engineering & few-shot prompting
- Chain of Thought reasoning
- Structured outputs, JSON mode & function calling
- Local models with Ollama & Pydantic
05
Phase 4 · RAG — Retrieval Augmented Generation (Weeks 12–13)
- Embeddings & vector databases
- ChromaDB & Pinecone
- Semantic search, chunking & hybrid search
- Building RAG APIs with FastAPI
06
Phase 5 · AI Agents (Weeks 14–15)
- Custom tools & function calling
- ReAct agents
- LangChain & LangGraph basics
- Multi-agent patterns with CrewAI
07
Phase 6 · Deployment & Career Sprint (Week 16)
- FastAPI & Streamlit deployment
- Docker basics
- Portfolio, resume & LinkedIn for AI roles
- Mock interviews & internship prep
- Capstone: deployed AI product + demo video
Hands-on projects
- Student performance predictor (ML)
- Data storytelling dashboard
- Image classifier with PyTorch
- Sentiment Analysis Classifier using Hugging Face
- CLI Chatbot with OpenAI & Anthropic
- Resume Analyzer with structured outputs
- Semantic PDF Search Engine (RAG)
- Research Agent with custom tools
- Capstone: Deployed AI Agent product
Tools you'll use
PythonJupyterPandasscikit-learnPyTorchHugging FaceOpenAIAnthropic ClaudeOllamaLangChainLangGraphChromaDBPineconeFastAPIStreamlitDockerGitHub
Career outcomes
- Advanced certification in Gen AI & Agentic AI Trainee
- Junior Data Analyst
- AI Intern
- GenAI Developer Intern
- Research Assistant
Career guidance
Portfolio reviews, resume workshops, LinkedIn optimization, mock interviews, and internship guidance tailored for students entering the AI job market.
Certificate of completion
Earn a GeekX United Certificate of Completion — shareable on LinkedIn and your student portfolio — after finishing all modules, projects, and the deployed capstone.