Applied GenAI: RAG, Vector Databases, Workflow Automation & Custom Agents
Build a real retrieval-augmented chatbot from scratch: embeddings, pgvector search, a free-tier LLM, n8n automation, and custom agents -- using this site's own live chatbot as the worked example.
Ends with a final quiz. Score 70% or better and you can download a completion certificate in your own name — shareable on LinkedIn, verifiable by its certificate code.
Every paid purchase (not a free/promo enrollment) includes a free 1-hour consultation call — after paying, contact me on LinkedIn or email with a screenshot of your order to redeem it.
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A minimum price of ₹999 applies — or use an active promo code above for free access.
Sign in with Google to enroll — it's how access gets tied to your account and how promo codes can be checked.
Log in with GoogleA hands-on course covering generative AI fundamentals, retrieval-augmented generation (RAG) architecture, vector databases (with a deep dive into pgvector), setting up a capable LLM without paying for API access, automating AI pipelines visually with n8n, and building custom tool-calling agents. The capstone walks through exactly how this portfolio's own AI chatbot widget is built end to end -- the same embeddings, the same vector search, the same free-tier model -- so every concept is tied to a real, running system rather than a toy example.