12-Week AI Program
AI: Zero to Hero
12-Week “Zero to Hero AI Expert” Agenda
A complete journey from programming fundamentals to deploying advanced AI systems, designed for career transformation.
Phase 1 – Foundation (Weeks 1–3)
Core skills, AI math basics, career setup.
Week 1 – Orientation & Career Foundation
- Introduction to AI landscape (ML, GenAI, Agents, Data Engineering).
- Career vision: Where do you fit? (Engineer, Analyst, Researcher, Applied AI).
- Resume baseline creation (before/after tracking).
- Real-world scenario: How big companies onboard new AI talent.
Week 2 – Math for AI (Part 1: Essentials)
- Linear Algebra (vectors, matrices, transformations).
- Probability basics (conditional probability, Bayes theorem).
- How these are used in AI models (recommendations, predictions).
- Parallel Learning: Case study of how Netflix uses linear algebra for recommendations.
Week 3 – Programming & Data Skills
- Python for AI (NumPy, Pandas, Matplotlib).
- SQL basics for data extraction.
- Introduction to Jupyter Notebooks & GitHub.
- Real-world scenario: Data wrangling task from healthcare or finance.
Phase 2 – Core AI/ML Skills (Weeks 4–7)
Machine learning theory + hands-on mini projects.
Week 4 – Math for AI (Part 2: Applied)
- Calculus (derivatives, gradients, optimization).
- Statistics for AI (distributions, hypothesis testing).
- How optimization drives neural networks.
- Mini project: Implement gradient descent in Python.
Week 5 – Classical Machine Learning
- Supervised learning: regression, classification.
- Unsupervised learning: clustering, dimensionality reduction.
- Tools: scikit-learn.
- Real-world project: Predict insurance claims fraud / customer churn.
Week 6 – Deep Learning Basics
- Neural networks: forward/backward propagation.
- Activation functions, loss functions, optimizers.
- Frameworks: TensorFlow / PyTorch intro.
- Mini project: Build an image classifier (cats vs dogs).
Week 7 – GenAI Foundations
- Transformers, embeddings, attention mechanism.
- Large Language Models (LLMs) in practice.
- Hands-on: Use OpenAI API or HuggingFace models.
- Scenario: Building a customer support AI chatbot.
Phase 3 – Advanced & Real-World AI (Weeks 8–10)
AI in production, scaling, and applied projects.
Week 8 – AI in Data Engineering & Pipelines
- ETL for AI projects.
- Streaming data (Kafka basics).
- Building AI-ready datasets.
- Scenario: Stream patient/provider data → preprocess → AI model.
Week 9 – Advanced AI Applications
- Generative AI (text-to-image, RAG, agents).
- Fine-tuning LLMs for specific industries (healthcare, finance).
- Mini project: Build a RAG pipeline with your own dataset.
Week 10 – AI Ethics, Security & Compliance
- Responsible AI & bias mitigation.
- Security in AI applications.
- Real-world case study: AI in banking (regulation + compliance).
Phase 4 – Career & Capstone (Weeks 11–12)
Industry readiness, project delivery, and placement prep.
Week 11 – Capstone Project (Build Your Own AI System)
- Choose one: AI chatbot for healthcare members, Fraud detection AI in insurance, or Real-time recommender system.
- Team-style development (GitHub + Agile + CI/CD).
- Mock demo presentation.
Week 12 – Career Launch & Job Replacement Prep
- Resume polishing (AI-ready portfolio).
- LinkedIn optimization.
- Mock interviews (technical + behavioral).
- Industry role mapping (Data Engineer → AI Engineer → AI Expert).
- Final showcase of projects to mentors/peers.