₹30,000All-inclusive — covers the full 16-week bootcamp, live mentor sessions, capstone reviews, certificate, and placement support. EMI plans available via Razorpay at checkout.
Enrol now — ₹30,000
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AI Engineer Bootcamp
A 16-week live mentor-led bootcamp covering Python, machine learning, deep learning, LLMs, and AI agents — with deployable projects that show you can build, not just talk.
16 weeksBeginners to advancedLive + LabCohort 15-20Placement support
By the end of this program
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.
Curriculum
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)
Python fundamentals for ML, NumPy, Pandas, matplotlib/seaborn, data cleaning, EDA. Project: End-to-end EDA on a real dataset, published as a notebook.
Module 2 · Classical machine learning (Weeks 4-7)
Linear/logistic regression, decision trees, random forests, gradient boosting, clustering. Evaluation, validation, feature engineering. Project: Predictive model deployed as an API.
Module 3 · Deep learning (Weeks 8-11)
Neural networks, backpropagation, PyTorch, CNNs, transformer intuition, fine-tuning small models. Project: Image classifier or text classifier, deployed.
Module 4 · LLMs & prompt engineering (Weeks 12-14)
Foundation models, prompting patterns, few-shot, structured outputs, evaluation. Project: A real LLM-powered tool — chatbot, summariser, or code reviewer.
Module 5 · RAG, agents & tools (Weeks 15-17)
Embeddings, vector search, retrieval-augmented generation, tool/function calling, multi-step agents. Project: An agent that reads, decides, and acts on real data.
Module 6 · Deploy, interview, capstone (Weeks 18-20)
Model serving, monitoring, cost & latency, basics of MLOps. System design with ML, interview prep, capstone build and demo day.
Investment
Pricing & EMI options
₹30,000
Enrol now — ₹30,000FAQ
Questions about the program
Do I need a strong math background?
Basic comfort with high-school math is enough. We refresh linear algebra, probability, and calculus only as needed — you don't need to be a math major. We focus on intuition and code, not proofs.
Will I have GPU access during training?
Yes. We provide Colab Pro credits and access to cloud GPU credits for the deep learning and LLM modules. You won't be blocked by hardware.
Is this program right for someone targeting AI/ML roles specifically?
Yes. The curriculum is built around the job market for AI engineer / ML engineer / applied AI roles in 2026 — not just academic ML. We focus on what you'll actually be asked to do on day one.
I'm a working professional. Can I do this part-time?
Yes — the part-time cohort runs evenings + weekends. Expect 12-15 hours per week. Many of our students join while working full-time and finish placement-ready.