Project 1
Document Q&A chatbot
A RAG chatbot that answers questions from your uploaded documents and cites sources.
- RAG
- Embeddings
- Citations
Data, AI & Cloud · Builder
Generative AI Course LLMs, RAG & Agents
Build applications on top of large language models. Three months of prompt engineering, retrieval-augmented generation, embeddings and AI agents, shipping real gen-AI apps grounded in real data, taught by engineers who deploy them for clients.
Build grounded LLM apps
Design real AI agents
Placement & freelance support
Program snapshot
Admissions open- Duration
- 3 months · 120 guided hours
- Mode
- Online live or classroom, Aligarh
- Level
- Beginner to intermediate
- Schedule
- Evening & weekend batches
- Certificate
- Cyber Warrior Certified GenAI Developer
- You build
- RAG apps, agents, gen-AI tools
Fees from
₹32,000 incl. GST, full program
What a generative AI course teaches
A generative AI course teaches you to build applications powered by large language models (LLMs) like those behind ChatGPT and Claude: how to prompt them well, ground them in your own data with retrieval-augmented generation, connect them to tools as AI agents, and deploy them safely. This three-month program is for builders who want to ship real gen-AI products, not just chat with them.
120h
Guided Hours
6+
GenAI Apps Shipped
4.9/5
Rating, 153 Reviews
100%
Build-Focused
Who this generative AI course is for
You do not need a machine learning background. You need to be able to write basic Python and want to build with AI.
Developers adding AI to products
Web, backend and app developers who want to build LLM features into what they already ship.
Graduates targeting gen-AI roles
Graduates who want to enter the fastest-growing area of AI without a deep ML research background.
Founders and freelancers
People who want to build and sell AI products or offer gen-AI services to clients.
Professionals adopting AI at work
Analysts, marketers and operators who want to build real AI tools for their team, not just use them.
Learning outcomes
What you can build after this generative AI course
Outcomes are shipped gen-AI apps, because the course is graded on working products.
01
Engineer reliable prompts
Design prompts and prompt patterns that produce consistent, useful output, and evaluate them properly.
02
Build RAG applications
Ground an LLM in your own documents with embeddings and vector search so answers cite real sources.
03
Design AI agents
Give models tools and let them plan and act, with the guardrails that make agents safe.
04
Integrate LLM APIs
Work with OpenAI, Anthropic and open models, handling cost, latency and streaming.
05
Add safety and evaluation
Build guardrails, handle hallucination and evaluate gen-AI output rather than hoping.
06
Ship gen-AI products
Deploy your apps with a real interface so anyone can use them.
Syllabus
Request the detailed syllabus PDF
Generative AI course syllabus
Seven modules over three months, every one ending in a shippable build. The course ends with a deployed gen-AI capstone.
7
Modules
120
Guided hours
The mental model you need: what LLMs are, what they can and cannot do, and how to work with them.
- What is generative AI
- How transformers and LLMs work
- Tokens, context and limits
- Capabilities and failure modes
- The AI tool landscape
- Python setup for AI
- Calling your first LLM API
- Cost and model selection
Module outcome: You call multiple LLM APIs and compare their behaviour.
Getting reliable, useful output from models, the core skill of gen-AI development.
- Prompt structure and roles
- Few-shot and chain-of-thought
- Structured output (JSON)
- System prompts and constraints
- Prompt patterns and templates
- Reducing hallucination
- Prompt evaluation
- Prompt version control
Module outcome: You build a prompt library with tested, structured outputs.
Teaching models about your data, the foundation of grounded AI.
- What embeddings are
- Generating embeddings
- Vector databases (Pinecone, Chroma)
- Semantic search
- Chunking strategies
- Similarity and retrieval
- Hybrid search
- Evaluating retrieval quality
Module outcome: You build a semantic search over a document set.
The most common production gen-AI pattern: answers grounded in your own content.
- The RAG architecture
- Grounding and citations
- Building a RAG pipeline
- Handling no-answer cases
- Reducing hallucination with RAG
- Multi-document retrieval
- RAG evaluation
- Frameworks: LangChain, LlamaIndex
Module outcome: You ship a RAG chatbot that cites its sources.
Letting models act, and doing it safely.
- What an AI agent is
- Tool and function calling
- Planning and reasoning
- Multi-step workflows
- Guardrails and confirmation
- Memory and state
- Agent frameworks
- When not to use an agent
Module outcome: You build an agent that uses tools to complete a task.
Making gen-AI reliable enough to ship, and knowing when to customise a model.
- Guardrails and moderation
- Prompt injection defence
- Evaluating gen-AI output
- Building an eval set
- Fine-tuning basics
- Open models and local LLMs
- Data privacy in gen-AI
- Responsible AI
Module outcome: You build an evaluation harness for a gen-AI app.
A deployed gen-AI product plus portfolio and career guidance.
- Capstone: build a real gen-AI app
- RAG or agent, grounded and evaluated
- Deploy with a real interface
- Presentation to a panel
- Portfolio and GitHub
- GenAI freelance and job paths
- Interview preparation
- Placement pipeline onboarding
Module outcome: You ship and present a deployed gen-AI application.
The generative AI toolkit
The tools that power production gen-AI, with API credits provided for the labs.
Core
- Python
- OpenAI API
- Anthropic Claude API
- Hugging Face
Frameworks
- LangChain
- LlamaIndex
- OpenAI SDK
Vector & Data
- Pinecone
- Chroma
- FAISS
- pgvector
Build & Deploy
- Streamlit
- FastAPI
- Gradio
- Git & GitHub
- Vercel
Portfolio work
Gen-AI projects for your portfolio
Six shipped gen-AI apps, the kind clients and employers pay for right now.
Project 2
Semantic search engine
Search across a document set by meaning, not keywords, with a clean interface.
- Vector DB
- Search
Project 3
Tool-using AI agent
An agent that plans and uses tools such as web search or a calculator to complete tasks.
- Agents
- Tool use
Project 4
Content generation tool
A structured content generator with prompt templates and quality guardrails.
- Prompting
- Structured output
Project 5
Gen-AI evaluation harness
A test suite that grades an LLM app against golden questions and refusals.
- Evaluation
- Guardrails
Project 6
Capstone gen-AI product
A deployed gen-AI app of your choice, grounded, evaluated and presented to a panel.
- Capstone
- Deploy
How the generative AI course runs
Six steps from enquiry to a deployed gen-AI app. The first two are free.
-
1
Book a counselling call
Twenty minutes with a gen-AI engineer who confirms your Python comfort and goals.
-
2
Get set up with API access
A guided session sets up Python and the LLM API keys and credits you will use throughout.
-
3
Ship something every module
Live sessions plus a working gen-AI build every fortnight, from prompts to agents.
-
4
Ground and evaluate
You learn to make gen-AI reliable with RAG, guardrails and evaluation, not just demos.
-
5
Deploy the capstone
A real gen-AI app deployed with an interface and presented to a panel.
-
6
Career and freelance support
Portfolio review, freelance guidance, mock interviews and referrals into gen-AI work.
Career outcomes
Generative AI jobs and opportunities
Gen-AI skills are in acute shortage, and this is one of the few areas where a strong portfolio can outweigh years of experience.
| Role | Typical salary (India) | What the job involves |
|---|---|---|
| Generative AI Developer | ₹6 to 18 LPA | Build LLM-powered features and products. The direct target role. |
| AI Application Engineer | ₹6 to 16 LPA | Integrate gen-AI into applications and workflows. |
| Prompt Engineer | ₹5 to 15 LPA | Design and optimise prompts and evaluation for gen-AI systems. |
| AI Product Builder / Founder | Variable / equity | Build and sell gen-AI products directly. |
| GenAI Freelancer / Consultant | Project-based | Deliver RAG and agent projects for businesses adopting AI. |
| Conversational AI Engineer | ₹6 to 16 LPA | Build chatbots and assistants grounded in company data. |
Where graduates of this track get hired
- AI startups
- SaaS companies
- Digital agencies
- Enterprises adopting AI
- Consulting firms
- Product teams
- Freelance marketplaces
- Cyber Warrior AI team
Salary and freelance income vary widely in this new and fast-moving field. Placement support is active help until hired, not a guarantee.
Placement support includes
- Resume, LinkedIn and GitHub portfolio review
- Mock technical and HR interviews with our engineers
- Referrals into our client and partner network
- Priority consideration for the Cyber Warrior internship
Choosing a format
Same tools and syllabus across every format. API credits are provided in all of them.
| Criterion | Online live | Classroom, Aligarh | Self-paced | Corporate batch |
|---|---|---|---|---|
| Live sessions per week | 3, evening or weekend | 3 at our Aligarh centre | Recorded only | Scheduled with team |
| Build review | Weekly, by an engineer | Weekly, in person | Self-submitted | Tailored |
| Doubt clearing | Saturday clinic + chat | Daily, in person | Weekly office hours | Dedicated trainer |
| Capstone review | Yes, with a panel | Yes, in person | Self-submitted | Tailored |
| Career support | Included | Included | Add-on | Not applicable |
| Best for | Anyone in India | Aligarh students | Budget self-starters | Company teams |
| Typical duration | 3 months | 3 months | Up to 6 months access | 2 to 6 weeks |
Want the deep-learning foundations too? Pair this with the AI & machine learning course.
Fees & batches
Generative AI course fees
One fee covering live teaching, LLM API credits and career support.
Next batches
New batches on the first Monday of every month, evening and weekend options.
Pay in instalments
Pay in 3 monthly instalments at no extra cost; the first confirms your seat.
Scholarships
Up to 25% merit scholarship based on the readiness check.
Generative AI Course · full program
₹32,000incl. GST, full program
Everything included
- 120 hours of live, practitioner-led sessions
- Recordings for 12 months
- LLM API credits for the labs
- Build review on every submission
- Six shipped gen-AI apps
- Deployed gen-AI capstone
- Freelance and interview guidance
- Cyber Warrior Certified GenAI Developer certificate
- Placement support until hired
Fees are indicative for the current cycle. Refunds follow our refund policy: full refund before the second live session.
Why learn generative AI with Cyber Warrior
We build RAG chatbots and AI agents for clients. You learn the grounding and evaluation that makes gen-AI safe to ship.
Grounding over hype
You learn to make gen-AI reliable with RAG, guardrails and evaluation, the difference between a demo and a product.
Real agent engineering
You build agents with tools and guardrails, taught by people who ship them.
You ship real apps
Every module produces a working, deployed build for your portfolio.
Freelance-ready
Gen-AI is one of the most in-demand freelance skills; we help you find clients.
Aligarh classroom, India-wide online
In-person build days in Aligarh and live online batches nationwide.
Small batches, individual review
Capped at 25 so every build gets reviewed.
Programs learners pair with this one
Every track in the Cyber Warrior programs catalogue shares the same faculty and project standard, so stacking two is common.
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Clear answers
Generative AI Course questions
The questions every applicant asks on the first counselling call.
It teaches you to build applications powered by large language models: prompt engineering, retrieval-augmented generation (RAG), embeddings and AI agents, plus how to deploy them safely. This is a builder course, not a theory course.
The full program fee is ₹32,000 including GST, payable in 3 monthly instalments at no extra cost. It covers live teaching, LLM API credits, build review and career support. Merit scholarships of up to 25% are available.
No. You do not need to know how to train models. You need basic Python and a willingness to build. The course focuses on using and orchestrating LLMs, not training them from scratch.
Prompt engineering is one module. The course also covers embeddings, vector search, RAG, AI agents, safety, evaluation and deployment, so you can build complete gen-AI applications.
You work with OpenAI and Anthropic Claude APIs and open models via Hugging Face, plus LangChain, LlamaIndex and vector databases like Pinecone and Chroma. API credits for the labs are included.
Yes. The online live format has the same tools, syllabus, build review and career support as the Aligarh classroom, with recorded sessions.
Yes, it is one of the most in-demand freelance skills right now. Businesses want RAG chatbots and AI tools built on their data, and the course covers finding and scoping that work.
Generative AI developer, AI application engineer, prompt engineer and conversational AI engineer, plus strong freelance opportunities. Salaries in India generally start around ₹6 LPA and rise quickly with a strong portfolio.
Start building with AI
Book a call with a gen-AI engineer. We will confirm the fit, show you what you will build, and tell you when the next batch begins.
Prefer WhatsApp or email? Contact the admissions team and we reply in under 3 minutes during working hours.