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Artificial Intelligence

Gen AI / Agentic AI — Build with LLMs. The Most In-Demand Skill of 2026.

Industry-aligned curriculum. Real agent applications. Job-ready in 10 weeks — taught by AI engineers who ship LLM apps to paying users.

10 weeks Online + Offline Python required
Generative AI neural brain visualization
Avg Salary
₹8–15 LPA
Demand in India
+120% YoY
Hiring
Google · Microsoft · Accenture AI Labs · Tiger Analytics · NVIDIA Partners
Curriculum

What You'll Learn

Eight modules, ten weeks — every concept anchored by code that calls a real LLM API on day one.

  • What an LLM actually is, demystified
  • Tokenization and the cost of every prompt
  • Attention and the transformer — the intuition
  • Open vs closed models — when each makes sense
  • Model providers: OpenAI, Anthropic, Mistral, open-source
  • Zero-shot, few-shot, and chain-of-thought
  • System prompts and persona design
  • Structured output: JSON mode, schemas, validation
  • Prompt templates and reusable patterns
  • Adversarial prompting and prompt injection defence
  • Why RAG beats fine-tuning for most apps
  • Chunking strategies and metadata design
  • Embedding models and similarity search
  • Hybrid retrieval: keyword + vector
  • Evaluating RAG quality with golden sets
  • Pinecone, Chroma, Weaviate compared
  • Indexing strategies and recall vs latency
  • Metadata filtering and namespaces
  • Self-hosting Chroma for prototypes
  • Production patterns and cost control
  • LangChain core: chains, prompts, parsers
  • LlamaIndex: query engines and indexes
  • Memory, callbacks and streaming
  • LangSmith for tracing and evaluation
  • When to drop frameworks and call APIs directly
  • ReAct pattern: reason + act loops
  • Tool/function calling — OpenAI and Claude
  • Designing safe, scoped tools
  • Error handling and self-correction
  • Hands-on: a research agent with browsing
  • Single-agent vs multi-agent trade-offs
  • CrewAI and AutoGen architectures
  • Roles, planners and critics
  • Inter-agent messaging and termination
  • Where multi-agent breaks (and how to recover)
  • FastAPI backend for an LLM app
  • Streaming responses and websockets
  • Evals: regression tests for prompts
  • Cost, latency and rate-limit handling
  • Capstone: a deployed agent on your domain
Meet Your Trainer

Taught by someone who ships, not just speaks.

KR

Karthik R.

AI/ML Architect · 6+ Years

Six years shipping ML and now LLM applications across SaaS and consulting. Has built two production RAG systems serving thousands of daily queries and runs the Hyderabad LLM-builders meetup. Trained 200+ engineers now working on AI teams across India and abroad.

in · View on LinkedIn →
Tools & Technologies

The full AI toolkit, hands on.

Logos shown as text-style placeholders pending official permissions.

OpenAI API
Anthropic Claude API
LangChain
LlamaIndex
Pinecone
Hugging Face
Python
FastAPI
Where You'll Land

Roles our Gen AI alumni step into.

AI Engineer

₹10–18 LPA

Build production LLM applications — agents, RAG, evals, end-to-end.

LLM Developer

₹8–14 LPA

Integrate LLMs into existing products — pick models, design prompts, ship features.

Prompt Engineer

₹7–12 LPA

Craft the prompts and pipelines that turn raw LLMs into reliable, business-ready tools.

AI Solutions Architect

₹14–25 LPA

Design enterprise AI architectures — pick patterns, set guardrails, mentor the team.

FAQ

Quick answers, no fluff.

Yes — comfortable Python is required. If you don't have it yet, start with our Python course (8 weeks) and roll into Gen AI right after — many students do.
Yes — a Sunadh completion certificate after the capstone agent app, plus we share verified credential paths from major model providers as they roll out.
We offer 100% placement assistance — interview prep, resume reviews, and intros to 500+ hiring partners. AI roles are the hottest market in 2026 — we're seeing 80%+ placement within 90 days.
Course starts from ₹32,999. No-cost EMIs available across major banks. API credits for OpenAI and Anthropic are included in the fee for the duration of the course.
Yes. Every Gen AI batch runs hybrid — attend in classroom one week, online the next. Switch as your schedule needs, no extra fee.
Every session is recorded and shared the same evening. You can also sit in any other ongoing batch to recover that topic in person.
Yes — a deployed agent app on a domain of your choice by week ten, with public demo URL and GitHub repo. This is the work hiring managers actually want to see.
New batches start every two weeks at both Ameerpet branches. Demand is high — book a free demo soon to lock in the next slot.