Learn AI by shipping it.
Project-first courses and real-world builds that take you from your first model to production agents — with architecture, milestones and deployment in every one.
A path from zero to production
Five stages, each with a course to learn it and projects to prove it.
Foundations
Python, maths and statistics — the parts you will actually use.
Machine learning
Classical models, evaluation and your first deployed API.
Generative AI
LLMs, prompting, embeddings and retrieval done properly.
Agents
Tool use, memory, multi-agent systems and MCP.
Production
MLOps, LLMOps, guardrails, evals and cloud deployment.
Start with a course
Agentic AI Engineering with LangGraph & MCP
Design, build and ship multi-agent systems that do real work — safely.
Production RAG Systems
Retrieval that holds up on real documents, real users and real evaluation.
Machine Learning & NLP: Zero to Deployment
The theory, the maths and the code — then ship it.
Build what companies actually need
Governed agents, production RAG, data pipelines and deployed models — each with a full architecture and build plan.
Governed agentic RAG over annual reports on Databricks
Ask a question about a listed company and get an answer built only from its annual report — every claim footnoted, and a refusal when the filing doesn’t say.
Governed multi-agent returns & refund triage for e-commerce
A team of agents reviews every return request, auto-approves the clean ones and routes risky or expensive cases to a human fraud desk.
HR policy assistant with hybrid search on Google Cloud
Employees ask about leave, travel or benefits and get a short answer with the exact policy clause — across PDFs, Word files and slide decks.
AI pull-request reviewer
A GitHub app that reads each pull request in context, flags real bugs and risky changes, and leaves inline comments a human would actually keep.
Enterprise advanced RAG: hybrid search, HyDE, self-correction and Text-to-SQL
Every advanced retrieval technique in one system, with an evaluation harness that shows which ones actually help on your data.
Python mega project: personal AI voice assistant
Build your own desktop assistant that opens apps, searches the web, reads the news, sets reminders and answers questions — all by voice.
Turn your teams into people who ship AI.
We design and deliver AI training around the outcome your business needs — an internal agent in production, a modern data stack, or two hundred managers who can scope AI work with confidence. Built with your L&D team, taught by practitioners, measured by what your people build.
Leadership
Half-day – 2 days
Product & programme managers
1 – 2 weeks
Engineers & data teams
4 – 8 weeks
Business functions
8 – 16 weeks
Rajat Chaudhary
Founder & Lead Instructor
Rajat leads ShipStack’s curriculum and its corporate programmes. Every course and project here is built the way teams actually ship software: a real problem, a working system, and a deployment you can show.
Frequently asked
Are the courses suitable for complete beginners?
Yes. Foundation courses start from zero and every course lists its prerequisites. Each project is tagged Beginner, Intermediate or Advanced so you can pick the right next step.
What makes a ShipStack project different from a tutorial?
Every project is a realistic business scenario with a defined architecture, a build plan in milestones, and a deployment step. You finish with a working system you can demo — not a notebook.
Do you train teams inside companies?
Yes. Our corporate programmes are designed around your outcomes, your data and your tools, and are delivered on-site, online or hybrid. See Corporate Training for how we work.
When do courses and projects open?
We are rolling them out one by one. Each page shows its current status — leave your email on any course or project and we will tell you the moment it opens.
Ready to build something real?
Pick a course to learn the skills, or jump straight into a project and learn by shipping.