AI Engineer Program
A 5-month live mentor-led program covering Python, machine learning, deep learning, LLMs, and AI agents — with deployable projects that show you can build, not just talk.
You will be able to…
Work fluently in Python for ML
NumPy, Pandas, vectorised computation, data wrangling, visualisation — production-grade Python, not just notebooks.
Train and evaluate ML models
Regression, classification, clustering, evaluation metrics, bias/variance, hyperparameter tuning, cross-validation.
Build deep learning models
Neural networks from scratch, PyTorch fundamentals, transformer intuition, training loops, GPU basics.
Ship real LLM applications
Prompt engineering, RAG pipelines, embeddings, vector stores, function calling, agents that actually do things.
Deploy & operate models
Model serving (FastAPI, vLLM), basic MLOps, observability, cost & latency tradeoffs in production.
Crack AI engineer interviews
Coding rounds, system design with ML, model-design discussions, behavioural prep, mock interviews with mentors.
Six modules. Twenty weeks. Built around shippable AI.
We don't stop at Jupyter notebooks. Every module ends with a deployable AI artefact.
Module 1 · Python & data toolkit (Weeks 1–3)
Module 2 · Classical machine learning (Weeks 4–7)
Module 3 · Deep learning (Weeks 8–11)
Module 4 · LLMs & prompt engineering (Weeks 12–14)
Module 5 · RAG, agents & tools (Weeks 15–17)
Module 6 · Deploy, interview, capstone (Weeks 18–20)
AI you can demo, not just diagram
End-to-end EDA & ML model
Real dataset, real insights, deployed prediction API.
Deep learning classifier
PyTorch model on image or text data. Trained, evaluated, deployed.
LLM-powered application
Real use case — chatbot, summariser, code reviewer. Live demo.
Production AI agent
An agent with tools, memory, and real-world data access. Deployed, monitored.
The AI stack of 2026
Pricing & EMI options
Pricing is finalised per cohort. Talk to our advisor for current rates, available discounts, and EMI plans.