Free webinars

90 minutes. Live. Free.

The best way to know us before you commit: a practical session on how AI applications are actually built, with a live engineering demonstration and time for your questions. Pick the one that fits where you are.

FREE · LIVE

How to Become an AI Application Developer

A practical roadmap for college students and early-career developers who want to move from using AI tools to building real AI applications.

90 minutesLeads into Step 1: Explore
Register free
FREE · LIVE

From Software Engineer to AI Product Engineer

How IT professionals can build real AI-powered products — beyond chatbots and prompting.

90 minutesLeads into Step 2: Build
Register free
FREE · LIVE

What AI Actually Changes in Software Engineering

Most teams have adopted AI at exactly one point in the lifecycle — a developer with an autocomplete plugin. That's the smallest win available.

90 minutesLeads into Step 3: Engineer
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How it works

Three steps to your free seat

1. Register

Pick a session and share your name and WhatsApp number. It takes under a minute.

2. Get your link

Your personal join link and reminders arrive on WhatsApp before the session.

3. Join live

90 minutes with a live demo and time to ask the mentor your questions.

Your host

Hosted 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

The kind of demo you'll see live

Real recordings from our labs: running AI apps, code and measured results.

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
Ready to build?

See the 3-step journey

Explore → Build → Engineer. Hands-on workshops on industry use cases. No programming experience required.

See the programs