For teams & colleges

AI engineering training, built around your team.

The same hands-on journey, delivered for your engineers or students, live online or on-site, with labs built around your stack and, for companies, one of your real use cases.

Companies

Engineering teams

Upskill developers, testers and architects to build and run AI systems responsibly.

  • Any of the three workshops, or a custom combination
  • Labs on your stack and a use case you choose (synthetic data, no confidential IP)
  • Enterprise AI Engineering for leads and architects: evaluation, security, LLMOps, governance
  • Post-training architecture review session for your team
Colleges & universities

Campus programmes

Give final-year and postgraduate students practical, portfolio-ready AI engineering skills.

  • Explore and Build together as one hands-on programme
  • Faculty development sessions on teaching applied AI
  • Project reviews and verifiable certificates for every student
  • On-campus or live online
How it works

From first call to trained team

Scoping call

Your goals, team size and level, stack, preferred dates and format.

Proposal

A tailored agenda, use case, schedule and fixed price in writing.

Delivery

Live, hands-on sessions with the mentor reviewing your team's work in the labs.

Follow-up

Certificates, project reviews and recommendations for next steps.

Who trains your team

Led by a practising AI engineer

Dr. Gajanan

Dr. Gajanan

Lead Mentor · Machine Learning, Generative AI & Agentic AI

14+years in ML & AI
ML→GenAI→Agentsthe full arc of modern AI

Designs the curriculum and leads the hands-on labs, helping participants think through problems the way an AI engineer does instead of memorising tools.

Machine learningGenerative AIAgentic AI systemsPython for AI
Inside the labs

What your team will build

Real recordings from our labs: working AI applications, code and measured results, not slides.

RAG lab

A documentation assistant, built end to end

A lab project: FastAPI backend, Chroma vector store and Llama 3 via Groq, answering questions about LangChain documentation.

RAGFastAPIChromaLlama 3
RAG evaluation lab

Measuring answer quality, not guessing

A lab notebook: a local FAISS knowledge base, a RAG pipeline on Groq LLMs, and RAGAS metrics to evaluate the answers. Shown at 2.5× speed.

RAG evaluationRAGASFAISSGroq
Request a proposal

Tell us about your team

We reply within one working day with questions or a draft agenda. Invoices are issued by Vithupro Infotech Pvt. Ltd.

Request a proposal

We reply within one working day.

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FAQ

Questions from teams

How many participants can join?

We size each batch so mentors can review everyone's work, and split larger groups into parallel batches. Tell us your numbers and we will plan it.

Can you use our own use case?

Yes, for company programmes we design the labs around a use case you choose, using synthetic or non-confidential data. We never need access to your production systems.

Online or on-site?

Both. Live online works well for distributed teams; on-site sessions can be arranged.

How is it priced?

Per programme, based on group size, duration and customisation. You get a fixed written quote after the scoping call.