100% Live & 100% Online · Instructor-led

Professional Program in Generative AIBuild with GenAI.Not Just Use It.

Go beyond prompting. Learn Python for GenAI, LLM APIs, embeddings, RAG, agents and deployment, and ship real AI products with LangChain, LlamaIndex and the OpenAI, Gemini and Claude APIs.

docs → embeddings → RAG app
Mode100% live & online
ClassesInstructor-led, real time
WhoDevs, engineers, techies
Fees & next batchFee on request →
How you learnLive instructor-led classesCode-along labsWeekly buildsDemo day for your AI productLearn from anywhere
Who it's for

For people who want to build AI

This is the hands-on builder track. Basic programming helps; we bring your Python up to speed for GenAI work.

01

Developers & engineers

Add LLMs, RAG and agents to your stack and build AI features that ship.

02

CS & IT students

Graduate with deployed GenAI projects, not just theory.

03

Data & analytics folks

Move from dashboards to AI apps powered by your data.

04

Tech founders

Prototype and launch a GenAI MVP without waiting on a team.

Tools & stack

The GenAI builder stack. Hands on.

Hands on keyboard with the stack teams actually use.

PY

Python for GenAI

The language behind almost every AI app.

API

OpenAI, Gemini & Claude APIs

Call frontier models from your own code.

EMB

Embeddings & vector DBs

Semantic search with tools like Pinecone, Chroma or pgvector.

RAG

RAG

Ground answers in your own documents.

LC

LangChain & LlamaIndex

Frameworks for chains, retrieval and agents.

AGT

AI agents & tool use

Models that call tools and complete tasks.

FT

Fine-tuning basics

When and how to adapt a model to your data.

GEN

Image & voice gen

Generate images, speech and voice experiences.

OPS

Eval & deployment

Test quality, then ship with APIs and the cloud.

Tool names are trademarks of their owners. The exact tools may change as the industry evolves.

Syllabus

12 modules. Zero fluff.

Tap a module to see the topics, what you'll build and the tools you'll touch.

01Module 1LLM fundamentals
  • How large language models work
  • Tokens, context windows and costs
  • Model families and when to use which
  • Limits: hallucination and bias
02Module 2Python for GenAI
  • Python essentials refresher
  • Working with APIs and JSON
  • Notebooks, envs and packages
  • Async and streaming basics
03Module 3Prompt engineering for builders
  • System prompts and structured output
  • Few-shot and chain-of-thought patterns
  • Function calling basics
  • Prompt testing and versioning
04Module 4Working with LLM APIs
  • OpenAI, Gemini and Claude APIs
  • Streaming, tools and JSON mode
  • Rate limits, retries and costs
  • Choosing models for a use case
05Module 5Embeddings & vector databases
  • What embeddings are
  • Chunking strategies
  • Vector DBs and similarity search
  • Hybrid search basics
06Module 6Retrieval-augmented generation (RAG)
  • RAG architecture end to end
  • Retrieval quality and reranking
  • Citations and grounding
  • Common RAG failure modes
07Module 7LangChain & LlamaIndex
  • Chains, retrievers and memory
  • Document loaders and indexes
  • Building pipelines
  • When not to use a framework
08Module 8AI agents & tool use
  • Agent loops and planning
  • Tool calling and APIs
  • Multi-step workflows
  • Guardrails and human-in-the-loop
09Module 9Fine-tuning basics
  • Prompting vs RAG vs fine-tuning
  • Preparing training data
  • Fine-tuning a small model
  • Measuring the gains
10Module 10Image & voice generation
  • Image generation APIs
  • Speech-to-text and text-to-speech
  • Building voice interfaces
  • Multimodal inputs
11Module 11Evaluation & responsible AI
  • Evaluating LLM outputs
  • Test sets and automated evals
  • Safety, privacy and bias
  • Responsible AI practices
12Module 12Deployment & capstone
  • Building an API with FastAPI
  • Frontends with Streamlit or Next.js
  • Deploying to the cloud
  • Monitoring cost and quality

Module order and depth may be tuned per batch. Your counsellor will share the exact plan.

Timeline

From first API call to deployed product

An indicative path from day one to demo day.

  1. Foundations

    LLM basics and Python for GenAI.

  2. Prompt & APIs

    Prompt engineering and multi-provider APIs.

  3. Retrieval

    Embeddings, vector DBs and RAG.

  4. Agents

    Frameworks, tool use and agent workflows.

  5. Level up

    Fine-tuning, multimodal and evaluation.

  6. Ship it

    Deploy your MVP and present at demo day.

Indicative plan. Exact duration, schedule and batch dates are shared by your counsellor.

Capstone projects

Six builds. All deployable.

Real builds for your GitHub and portfolio. Not quiz scores.

RAG

RAG chatbot on company docs

A chatbot that answers questions from a document set with citations.

Agents

Workflow automation agent

An AI agent that uses tools to complete a multi-step business workflow.

Content

Content-generation app

An app that generates on-brand text and images with guardrails.

Voice

Voice assistant

A voice interface with speech-to-text, an LLM and text-to-speech.

Evals

LLM evaluation dashboard

Automated tests that score your app's answers for quality and safety.

Capstone

Deployed GenAI SaaS MVP

Your own GenAI product, deployed live and presented at demo day.

Certification

Finish strong. Get certified.

SkillCircle Certificate + portfolio

Complete the modules and capstones to earn a SkillCircle Certificate of Completion, plus a GitHub portfolio of deployed GenAI projects that shows exactly what you can build.

The certificate is issued by SkillCircle. It is not a university degree or a government-accredited qualification.
Enquire Now →
Case studies & success stories

Your story goes here.

This program is new, so we won't fake it. These cards will be filled with real alumni journeys, shared with their permission.

Placeholder · Alumni story 1

Your story here

A real learner's journey will appear here after the first batch.

  • Background: to be added
  • Capstone built: to be added
  • Where they are now: to be added
Placeholder · Alumni story 2

Your story here

A real learner's journey will appear here after the first batch.

  • Background: to be added
  • Capstone built: to be added
  • Where they are now: to be added
Placeholder · Alumni story 3

Your story here

A real learner's journey will appear here after the first batch.

  • Background: to be added
  • Capstone built: to be added
  • Where they are now: to be added
Placement support

Interview-ready. Not just course-complete.

We offer a 5-interview guarantee, or we'll teach you free for 1 year (*T&C apply).

Placement support helps you prepare and connects you with openings, but getting hired depends on your skills, effort and interviews.

*Terms and conditions apply. Ask your counsellor for the full T&C.

What placement support includes

  • 1:1 mock interviews and technical rounds
  • GitHub and portfolio review
  • Resume and LinkedIn polish
  • Connects you with relevant openings
Fees

Fee on request. EMI available.

Fee on request

Fees depend on the batch and format you choose. Talk to a counsellor for the current fee and next batch dates.

Get the fee details →

Easy EMI via Bajaj Finance

Spread the fee into monthly instalments with EMI options through Bajaj Finance.

EMI is subject to eligibility and approval by Bajaj Finance. Ask your counsellor for current options.Check EMI options
FAQs

Questions? Fair.

Is this course live or recorded?

It is 100% live and 100% online, with instructor-led code-along classes in real time.

How is this different from your other AI courses?

Our AI course for non-tech learners focuses on using AI tools, and Vibe Coding is about building apps with AI builders without code. This program is for builders who want to write code with LLM APIs, RAG and agents.

Do I need to know Python?

Basic programming knowledge helps. We include a Python for GenAI module to bring you up to speed.

Which models and frameworks will I use?

OpenAI, Gemini and Claude APIs, plus LangChain, LlamaIndex, vector databases and deployment tools.

Will API usage cost me money?

Most labs fit in free tiers or small credits. Your instructor will show you how to keep costs low.

What projects will I build?

Six projects including a RAG chatbot, a workflow automation agent, a content-generation app, a voice assistant and a deployed GenAI SaaS MVP.

Will I get a certificate?

Yes, a SkillCircle Certificate of Completion after you complete the modules and capstones.

What is the fee? Is EMI available?

The fee is shared on request by our counsellor. EMI is available via Bajaj Finance, subject to eligibility.

What happens if I'm not placed after the course?

Interviews are guaranteed. You can keep applying to openings shared on #JobCircle, and our counsellor will explain the placement support available after your course ends. If you don't clear 5 interviews, we'll coach you free for 1 year, no questions asked (T&C apply).

Stop prompting. Start building.

Talk to a counsellor about the next live online batch of the Generative AI program.