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Career Program · KPHB, Hyderabad & Online

Generative AI + Agentic AI

Build LLM applications and the AI agents that put them to work.

Go beyond chatting with AI. Learn how LLMs work, engineer reliable prompts, and build retrieval-augmented applications — then design agents that plan, call tools, remember context and coordinate with other agents, with the evaluation and guardrails production systems need.

  • Course fee ₹30,000
  • Batches 9:30 AM – 11:30 AM · 11:30 AM – 1:30 PM
  • 13 modules
  • 77 topics
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Generative AI + Agentic AI course at The Data School, KPHB, Hyderabad

What you will master

  • Explain how LLMs, tokens and context windows work
  • Design and test reliable prompts
  • Build applications on top of LLM APIs
  • Use embeddings and vector search
  • Build and evaluate RAG pipelines
Talk to an advisor
  • 13Modules
  • 77Topics covered
  • 8Learning outcomes
  • 10Tools & technologies
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Course Overview

What this program covers.

Go beyond chatting with AI. Learn how LLMs work, engineer reliable prompts, and build retrieval-augmented applications — then design agents that plan, call tools, remember context and coordinate with other agents, with the evaluation and guardrails production systems need.

Career relevance

Organisations are moving from AI experiments to AI products — and from answering questions to completing work. Engineers who can build grounded LLM applications and safe, observable agents are central to that shift.

Who it's for

Developers, data professionals and technically-minded learners who want to build real applications and agentic systems with large language models.

Prerequisites

Basic Python is recommended.

Learning outcomes

  • Explain how LLMs, tokens and context windows work
  • Design and test reliable prompts
  • Build applications on top of LLM APIs
  • Use embeddings and vector search
  • Build and evaluate RAG pipelines
  • Build agents that call tools and APIs
  • Design agent workflows with memory and context
  • Build multi-agent systems with evaluation and guardrails

Detailed Syllabus

13 modules. One clear path.

Every module, every topic. Expand a module to see exactly what you will learn.

13 modules · 77 topics

  1. Build an accurate mental model of what generative AI can and cannot do.

    What you will learn

    • What generative AI is
    • Transformers and LLMs at a high level
    • Tokens and context windows
    • Capabilities and limits
    • Hallucinations
    • Use cases

Learning Experience

How you will learn.

  • Instructor-led learning

    Structured sessions that explain the why, not just the how.

  • Hands-on exercises

    Practise every concept in code as you learn it.

  • Assignments

    Reinforce each module with focused, reviewed work.

  • Applied practice

    Combine multiple skills to solve realistic problems.

  • Portfolio development

    Package your work so employers can see what you built.

  • Interview preparation

    Practise technical questions and project walkthroughs.

Tools & Technologies

The stack you will use.

  • LLMs
  • Prompt Engineering
  • Embeddings
  • Vector Databases
  • RAG
  • APIs
  • AI Agents
  • Tool Calling
  • Multi-Agent Systems
  • Python

Projects

Projects you'll build.

Portfolio projects that bring the syllabus together — each ends with a GitHub repository you can show employers.

Generative AI

RAG Document Assistant

Teams keep knowledge in PDFs and documents that are slow to search. This project builds an assistant that answers questions from your own documents and shows where each answer came from.

What you'll build

  • Document ingestion and chunking pipeline
  • Embedding and vector index
  • Retriever with metadata filters
  • Answer generation grounded in retrieved context
  • Chat interface with source citations

You'll leave with: Working assistant · GitHub repository with README · Evaluation notes · Demo walkthrough

  • LLMs
  • Embeddings
  • Vector Databases
  • RAG
  • APIs
  • Python

Agentic AI

AI Research Agent

Research means searching, reading and summarising many sources. This project builds an agent that plans a research task, gathers sources with tools and writes a structured summary.

What you'll build

  • Planner that breaks a question into steps
  • Search and page-reading tools
  • Memory of findings so far
  • Report writer with a source list
  • Guardrails limiting steps and cost

You'll leave with: Working research agent · GitHub repository with README · Sample research reports · Demo walkthrough

  • AI Agents
  • Tool Calling
  • Memory
  • Workflows
  • LLMs
  • Python

Agentic AI

Multi-Agent Business Assistant

Real business tasks need several skills at once. This project builds a team of specialised agents coordinated by a supervisor to complete multi-step tasks.

What you'll build

  • Supervisor agent that routes tasks
  • Specialist agents for research, data and writing
  • Shared memory and state
  • Tool access with permission limits
  • End-to-end run evaluation

You'll leave with: Working multi-agent system · GitHub repository with README · Evaluation results · Demo walkthrough

  • Multi-Agent Systems
  • Workflows
  • Tool Calling
  • RAG
  • Memory
  • LLMs

Career Outcomes

Roles this program prepares you for.

Relevant roles for the skills you will build. Outcomes depend on individual effort, background and the job market.

  • Generative AI Engineer
  • Agentic AI Engineer
  • AI Application Developer
  • AI Automation Engineer

FAQ

Questions, answered.

Still unsure? An advisor can walk you through the program.

Where should I start if I am new to Generative AI + Agentic AI?

If you already know basic Python, start with Generative AI Foundations — the agentic modules build on it. If not, pick up Python basics first — an advisor can suggest the right starting point.

Is the program project-based?

Yes. Every module is paired with hands-on exercises, and the program builds towards portfolio projects that you can publish on GitHub and discuss in interviews.

Do I need to know how to code?

Yes, basic Python is recommended because you will build working applications and agents. You do not need prior AI or machine learning experience.

What learning modes are available?

Programs are designed around instructor-led learning. Talk to an advisor for the learning modes (online, classroom or hybrid) available for the next batch.

Does the program include interview preparation?

Yes. Interview preparation is part of the learning experience, covering technical questions, project walkthroughs and how to present your portfolio.

Where are Generative AI + Agentic AI classes held?

Classroom sessions run at The Data School, 4th Floor, MIG 549, Road Number 1, Above HDFC Bank, KPHB Colony, Kukatpally, Hyderabad — close to KPHB Colony Metro station. Live online and hybrid options are also available.

Can I attend a free demo class for Generative AI + Agentic AI?

Yes. Book a free demo class at our KPHB centre or online — there's no obligation to enrol. The centre is open Monday to Saturday, 9 AM to 9 PM.

What is the course fee, and when do batches start?

The course fee is ₹30,000. Classroom batches run Monday to Saturday, 9:30 AM – 11:30 AM or 11:30 AM – 1:30 PM. You can attend a free demo class first — book one online or call the centre, and an advisor will share the next start date.

Learn Generative AI + Agentic AI near you

Classroom batches Monday–Saturday (9:30 AM – 11:30 AM or 11:30 AM – 1:30 PM) at Road Number 1, KPHB Colony, Kukatpally — plus live online and hybrid options. Course fee ₹30,000.

Ready to Start Your AI Career?

Course fee ₹30,000. Speak with an advisor about the Generative AI + Agentic AI program, learning modes and upcoming batch dates.

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