What is Prompt Engineering and why does it matter?

Prompt Engineering is the skill of designing effective inputs to get high-quality outputs from large language models like GPT-4 and Claude. It is essential for building reliable AI applications and agents.

What is the duration of the Prompt Engineering course in Chennai?

The Prompt Engineering course is 2 months long. It is ideal as a standalone course or as a complement to our Generative AI or Applied AI courses.

What techniques will I learn in the Prompt Engineering course?

You will learn zero-shot, few-shot and Chain-of-Thought prompting, ReAct agent patterns, RAG pipeline design, prompt chaining and evaluation frameworks for LLM outputs.

What projects will I build in the Prompt Engineering course?

You will build an AI research assistant, a code review bot, a multi-step reasoning agent, a customer service automation tool and a RAG-powered knowledge base system.

Can non-technical people learn Prompt Engineering?

Yes. Prompt Engineering is one of the most accessible AI skills. No coding background is required to start, though we also teach Python integration for those who want to go deeper.

✨ Prompt Engineering Track

Prompt Engineering Course in Chennai — LLMs, RAG & AI Agents

Control how LLMs think, reason, and respond. Build reliable, production-grade AI applications using the most powerful models available today.

View Syllabus ↓

5 Modulescovered

4+ Projectsbuilt

OpenAI + LangChaintools

LLM Engineeroutcome

📚 Course Syllabus

Prompt Engineering Skills You'll Master

Every module is outcome-driven — you build something real at the end of each one.

LLM architectureTokenizationContext windowsTemperaturetop-pmax_tokensAnatomy of a prompt

Understand how LLMs process and generate text

Control output creativity with temperature and sampling

Design clear, structured prompts

Craft prompts that reliably produce the exact output you need

Zero-shotFew-shotChain-of-ThoughtReActTree-of-ThoughtsRole promptingPersona prompting

Make AI reason step-by-step through complex problems

Build multi-shot prompts for high accuracy tasks

Create consistent AI personas for products

Design prompts that break complex tasks into structured reasoning

OpenAI APIPrompt templatesLangChainLLMChainPromptTemplateContext chainingVersioning

Automate prompts programmatically with LangChain

Build parameterized, reusable prompt templates

Track prompt versions like code

Integrate and automate prompts in production systems

Eval metricsCoherenceRelevanceHallucination detectionContent safetyGuardrailsSelf-evaluation prompts

Measure prompt performance with quantitative metrics

Reduce hallucinations by 80%+ with grounding techniques

Build self-checking prompts that validate their own answers

Build safe, accurate, and auditable LLM pipelines

Email rewritingCode debuggingDocument summarizationCustomer service botRAG basics

Build production-grade LLM-powered tools

Combine prompts with external data sources

Deploy AI assistants as real applications

Ship two production-ready LLM-powered applications

🛠 Tech Stack

LLM Tools & Frameworks

Industry-standard tools you'll use throughout this program — exactly what employers want.

🤖

OpenAI API

GPT-4 / 3.5

🦜

LangChain

LLM orchestration

🌿

Anthropic Claude

Claude API

📦

Guardrails AI

Output safety

🔍

PromptLayer

Prompt tracking

⚡

FastAPI

App serving

🎯

Streamlit

UI layer

📊

MLflow

Experiment tracking

💻 Real Projects

LLM Applications You'll Build

Portfolio-ready projects that demonstrate your skills to recruiters from day one.

PROJECT 01

Intelligent Email Rewriter

Rewrite emails in different tones (formal, friendly, persuasive) using role prompting and style conditioning.

OpenAI APILangChainPromptTemplateStreamlit

✅ Deployed tone-adaptive writing assistant

PROJECT 02

Code Explainer & Debugger

Prompt GPT to analyze, explain, and auto-fix Python code bugs using Chain-of-Thought prompting.

OpenAI APIFew-shot CoTFastAPIPython

✅ Conversational code assistant deployed as API

PROJECT 03

Self-Checking QA Bot

Build a QA system that validates its own answers before returning them to the user.

LangChainOpenAISelf-eval promptsStreamlit

✅ Hallucination-resistant QA system

PROJECT 04

Document Summarization Pipeline

Summarize long documents in structured formats using map-reduce prompting and LangChain.

LangChainOpenAIPDF extractionFastAPI

✅ Production document processing pipeline

🎯 Transformation

AI Engineer Roles You'll Land

By the end of this program, you won't just have knowledge — you'll have career-changing proof.

✨

Prompt Engineer

Control any LLM with precision

🔒

Safe AI Builder

Reduce hallucinations and unsafe outputs

🚀

LLM App Dev

Build production LLM applications

🤖

GenAI Ready

Direct pathway into Generative AI

🏢 Placement Network

Our Students Work Here

⚡ Next Batch Closing Soon — Limited Seats

Start Your AI Journey Today

Join Prompt Engineering and build real-world skills that get you hired.

🔒 2-day risk-free trial · 30-day money back · No credit card required

Frequently Asked Questions

About the Prompt Engineering Course in Chennai

The Prompt Engineering course is 6–8 weeks long covering prompting techniques, LangChain, RAG pipelines, AI agent design and LLM application deployment.

You will learn OpenAI API, Anthropic Claude, LangChain, LlamaIndex, Pinecone, FAISS and Streamlit to build production LLM-powered applications.

This course suits developers, data scientists, product managers and anyone who wants to build LLM-powered applications using OpenAI, Claude, LangChain and RAG.

LLM engineers in India earn ₹10–22 LPA at entry to mid level. Specialists with agentic AI and production RAG experience can command ₹30 LPA and above.

You will build a RAG-based document Q&A system, an AI agent for automated research, a multi-modal LLM app and an LLM-powered code assistant.