5000+ Students Trained
100+ Corporate Clients
Industry-Vetted Curriculum
92% Placement Success
AI-Powered Learning
Institutional Partnerships
4.9/5 Student Rating
Cyber Security Excellence
5000+ Students Trained
100+ Corporate Clients
Industry-Vetted Curriculum
92% Placement Success
AI-Powered Learning
Institutional Partnerships
4.9/5 Student Rating
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Engineering

🤖 Agentic AI

Build AI That Acts.

5000+
Students Trained
92%
Placement Success Rate
8+
Agent Projects Built
4.9★
Average Student Rating
🧠

What Is an AI Agent?

An AI agent is an LLM-powered system that perceives its environment, plans multi-step actions, calls external tools, and autonomously drives toward a defined goal — without constant human instruction.

🔗

Why Agentic AI Matters Now

Companies are rapidly replacing rule-based automation with LLM agents that can reason over unstructured data, adapt to changing contexts, and handle entire workflows end-to-end.

🚀

The Career Opportunity

Agentic AI engineers are among the most sought-after professionals in 2025. Demand far outstrips supply — and CodEvo's program puts you at the bleeding edge of this skill gap.

The Most Advanced AI Engineering Program in India

Agentic AI is not a theoretical concept — it is already reshaping how software is built, how businesses operate, and what engineers are worth in the market. CodEvo's Agentic AI program is India's most current, hands-on curriculum for building autonomous AI systems with the exact frameworks and LLMs powering real products today.

You begin by mastering the LLM fundamentals that underpin all agentic behaviour — context windows, tool use, function calling, and prompt mechanics — before progressively learning to architect single-agent loops, multi-agent teams, RAG pipelines, memory systems, and finally full agent deployment on cloud infrastructure. Every session is grounded in building actual applications, not watching slides.

Whether you want to build an autonomous research assistant, a customer support agent that actually resolves tickets, a multi-agent content pipeline, or a code-writing copilot — this program teaches you the architecture, the frameworks, and the production engineering skills to ship it. Our instructors are actively building agentic systems professionally, not teaching from textbooks.

Bleeding-Edge Curriculum

Updated monthly to reflect the latest releases in LangChain, CrewAI, OpenAI Assistants API, and Anthropic's Claude tool use. You always learn what's current.

🤖

Multi-LLM Proficiency

Work hands-on with GPT-4o, Claude 3.5, Gemini 1.5, and open-source models like Llama 3 and Mistral — understanding when and why to choose each.

🏗️

8+ Production Agent Projects

From autonomous research agents to multi-agent sales pipelines — every project is designed to showcase real engineering capability in your portfolio.

☁️

End-to-End Deployment

You don't just build agents in Jupyter — you deploy them with FastAPI, Docker, and cloud infrastructure so they actually run in production.

Who Should Enroll?

This program is designed for learners with some programming foundation. Python basics and familiarity with APIs are beneficial — no prior AI experience required.

💻

Software Engineers

Backend, full-stack, or data engineers who want to integrate AI agents into their products and position themselves for AI engineering roles.

📊

Data Scientists & ML Engineers

Professionals with ML backgrounds looking to move beyond model training into building autonomous, reasoning AI systems that deploy in production.

🏢

Corporate AI Teams

Enterprise technology teams in BFSI, healthcare, retail, or logistics seeking to upskill on agentic automation to drive operational efficiency.

🚀

Founders & Product Builders

Startup founders and product managers who want to build AI-native products and understand agent architecture well enough to lead technical development.

🎓

CS / Engineering Graduates

Recent graduates with programming backgrounds who want to enter the job market with one of the most in-demand and highest-paid AI skill sets of 2025.

🔄

Automation Specialists

RPA and workflow automation professionals transitioning from rule-based tools like UiPath or Zapier to intelligent, LLM-powered agentic pipelines.

Course Modules & Syllabus

An 8-module curriculum progressing from LLM fundamentals and RAG through multi-agent systems, memory architectures, browser automation, and cloud deployment.

01

LLM Fundamentals & Architectures

Week 1–2 · Theory + API Hands-On
  • Transformer architecture deep-dive: attention, tokenisation, and context windows
  • How LLMs are trained: pre-training, RLHF, instruction tuning, and alignment concepts
  • OpenAI API, Anthropic Claude API, and Google Gemini API — setup and rate limits
  • System prompts, roles, temperature, top-p, and controlling generation behaviour
  • Tool use and function calling: how LLMs interact with external systems via JSON schemas
  • Open-source LLMs: Llama 3, Mistral 7B, and Phi-3 — running locally with Ollama
02

Prompt Engineering for Agents

Week 3 · Advanced Prompting
  • Chain-of-thought (CoT), tree-of-thought (ToT), and self-consistency prompting
  • ReAct (Reason + Act) framework — the foundation of all LLM agent loops
  • Structured output prompting: enforcing JSON schemas with Pydantic and instructor
  • Few-shot and zero-shot prompting strategies for task decomposition
  • Prompt injection attacks, adversarial inputs, and defensive prompting strategies
  • Evaluating prompt quality: LLM-as-judge, G-Eval, and human preference alignment
03

RAG & Vector Databases

Week 4–5 · Retrieval-Augmented Generation
  • Vector embeddings: what they are, how they encode semantic meaning, and distance metrics
  • Embedding models: OpenAI text-embedding-3, Cohere, and open-source sentence-transformers
  • Vector databases: Pinecone, Chroma, FAISS, Weaviate — CRUD, indexing, and ANN search
  • RAG pipeline architecture: document ingestion, chunking strategies, retrieval, and generation
  • Advanced RAG: HyDE, re-ranking with Cohere, query expansion, and contextual compression
  • Project: Multi-document intelligent Q&A system with source citation and confidence scoring
04

LangChain & LangGraph

Week 6–7 · Agent Orchestration
  • LangChain architecture: chains, runnables, LCEL, and the LangChain Expression Language
  • Tool creation and ToolCall integration — connecting agents to APIs, databases, and code
  • LangChain agents: ReAct agent, OpenAI Tools agent, and custom agent executors
  • LangGraph: stateful, graph-based agent workflows with conditional edges and cycles
  • Building multi-turn conversational agents with persistent state and context management
  • LangSmith: tracing, debugging, and evaluating LangChain pipelines in production
05

Multi-Agent Systems: CrewAI & AutoGen

Week 8–9 · Agent Collaboration
  • Multi-agent architecture: orchestrator, specialist agents, and critic-reviewer patterns
  • CrewAI: defining agents with roles, goals, and backstories — building collaborative crews
  • CrewAI tasks, processes (sequential vs hierarchical), and inter-agent communication
  • AutoGen: conversational multi-agent programming with GroupChat and UserProxyAgent
  • Agent-to-agent delegation, sub-agent spawning, and error-recovery strategies
  • Project: Multi-agent research and report-writing crew with web search and PDF export
06

Memory Systems & Long-Context Agents

Week 10 · Persistent Agent Memory
  • Types of agent memory: sensory, short-term (buffer), long-term (external), and episodic
  • Conversation buffer and summary memory with LangChain memory modules
  • Long-term memory with vector stores: storing, retrieving, and decaying memories over time
  • Entity memory: tracking named entities (people, companies, concepts) across sessions
  • MemGPT and LangMem: OS-style memory management for ultra-long agent contexts
  • Project: Personal AI assistant that remembers user preferences and past interactions
07

Web Agents & Browser Automation

Week 11 · Agentic Web Interaction
  • Browser automation with Playwright and Selenium — headless and headed modes
  • Web scraping agents: dynamic rendering, JavaScript execution, and anti-bot evasion
  • LLM-driven browser agents: Langchain Browser Agent and Playwright MCP integration
  • Form-filling, navigation, screenshot capture, and structured data extraction agents
  • Computer Use API (Anthropic) and GPT-4V for visual browser navigation
  • Project: Autonomous competitive intelligence agent that monitors rival websites daily
08

Agent Deployment, Monitoring & Capstone

Week 12–16 · Production + Portfolio
  • Wrapping agents as FastAPI services: REST endpoints, streaming responses, and WebSockets
  • Containerising agent apps with Docker and deploying to AWS ECS, Railway, or Render
  • Agent observability: tracing with LangSmith, logging with OpenTelemetry, and cost tracking
  • Safety, guardrails, and output validation: NeMo Guardrails and Guardrails AI
  • Capstone project: full-stack, deployed agentic application solving a real business problem
  • Portfolio review, GitHub optimisation, mock interviews, and placement drive

Types of AI Agents You Will Master

Every category of AI agent has distinct architecture patterns. You will build working examples of all of them throughout the course.

🔍

Research Agent

Autonomously searches the web, reads documents, synthesises findings, and produces structured research reports — replacing hours of manual research work.

LangGraph + Tavily
💬

Customer Support Agent

An LLM-powered agent connected to your product knowledge base, ticketing system, and CRM — it reads, reasons, and resolves support queries autonomously.

RAG + CRM Tools
💻

Code-Writing Copilot

An agent that understands codebases, writes functions, runs tests, debugs failures, and iterates until the code passes — a true pair programmer.

Code Interpreter + Git
📊

Data Analysis Agent

Connects to databases, writes and executes SQL, creates visualisations, and explains insights in plain language — on demand, without a data analyst.

SQL + Pandas + Plotly
📝

Content Pipeline Agent

A multi-agent crew that researches a topic, drafts an article, fact-checks it, formats it, and posts it to a CMS — a full editorial workflow, automated.

CrewAI + WordPress API
🌐

Web Browsing Agent

Navigates real websites, fills forms, scrapes dynamic content, monitors competitor pages, and summarises findings — like a digital employee browsing for you.

Playwright + GPT-4V

8+ Agent Projects You Will Build & Deploy

Each project is a complete, deployable application — not a tutorial exercise. Your portfolio demonstrates real production-grade agent engineering.

📄

Intelligent Document Q&A Agent

A RAG-powered agent ingesting 100+ PDFs and responding to natural language queries with cited sources. Deployed as a Streamlit app with source highlights.

LangChainPineconeOpenAIStreamlit
🔬

Autonomous Research & Report Writer

A CrewAI multi-agent system with a researcher, analyst, and writer agent. Given a topic, it searches the web, synthesises findings, and outputs a formatted PDF report.

CrewAITavilyGPT-4oWeasyPrint
🛎️

Customer Support Resolution Agent

An LLM agent connected to a knowledge base and ticketing system that classifies, routes, and resolves customer queries — escalating only when human judgment is needed.

LangGraphFastAPIZendesk APIClaude
🏦

Financial Data Analysis Agent

An agent that connects to a PostgreSQL database, writes SQL from natural language, generates Plotly charts, and delivers executive-level business summaries on demand.

LangChainPostgreSQLPlotlyGemini
🕵️

Competitor Intelligence Monitor

A Playwright-based web agent that monitors competitor websites, product pages, and pricing daily — then emails a structured diff report of what changed.

PlaywrightGPT-4VRedisSendGrid
🧑‍💼

Personal AI Chief of Staff

A long-memory personal agent that manages tasks, drafts emails, remembers context from past conversations, and proactively suggests actions based on your calendar and preferences.

MemGPTGmail APICal APILangGraph

Skills You Will Master

A complete Agentic AI engineering skillset — covering LLM APIs, orchestration frameworks, memory, deployment, and safety for production systems.

LLM API Integration
Prompt Engineering
Function Calling & Tool Use
RAG Pipeline Design
Vector Database Management
LangChain & LCEL
LangGraph Stateful Agents
CrewAI Multi-Agent Teams
AutoGen Conversations
LlamaIndex Pipelines
Agent Memory Systems
Browser & Web Agents
Playwright Automation
Agent Guardrails & Safety
FastAPI Agent APIs
Docker Deployment
LangSmith Observability
OpenAI Assistants API
Structured Output Parsing
Agent Cost Optimisation
Tech Stack

Tools & Frameworks
You Will Work With

Every tool below is used in production agentic systems at leading AI companies, startups, and enterprise technology teams worldwide.

LLMs & Model APIs
OpenAI GPT-4o Anthropic Claude 3.5 Google Gemini 1.5 Llama 3 (Meta) Mistral 7B Ollama (Local)
Agent Orchestration Frameworks
LangChain LangGraph CrewAI AutoGen (Microsoft) LlamaIndex Semantic Kernel
Memory & Vector Databases
Pinecone ChromaDB FAISS Weaviate MemGPT LangMem Redis (Cache)
Web Agents & Automation
Playwright Selenium Tavily Search API SerpAPI Computer Use API Browserbase
Deployment, Observability & Safety
FastAPI Docker LangSmith Guardrails AI NeMo Guardrails AWS ECS Streamlit

Where This Program Takes You

The demand for Agentic AI engineers is growing faster than any other engineering discipline. Our graduates are placed in the roles defining the next decade of software.

🤖

Agentic AI Engineer

Design, build, and deploy autonomous AI agent systems at AI-first startups, product companies, and consulting firms adopting LLM-based automation at scale.

₹12–28 LPA · Extreme Demand
🔗

LLM Application Developer

Build production LLM-powered applications — chatbots, copilots, document intelligence, and workflow automation tools — for SaaS platforms and enterprise clients.

₹10–22 LPA
🏗️

AI Solutions Architect

Design end-to-end AI architecture for enterprises — selecting the right LLMs, agent patterns, RAG strategies, and deployment infrastructure for each use case.

₹18–35 LPA Senior
🔬

AI Research Engineer

Work on frontier agent research at AI labs, university research groups, or corporate R&D teams exploring new agent architectures, benchmarks, and evaluation methods.

Research + Industry
💼

AI Automation Consultant

Help businesses identify, design, and implement AI agent solutions that automate workflows, reduce costs, and create competitive advantages across industry verticals.

High-Value Consulting
🚀

AI Product Builder / Founder

Launch your own AI-native product — from a niche SaaS agent to a full automation platform — with the technical depth to build it yourself and the knowledge to lead a team.

Entrepreneurship Track

What Makes This Program Different

Monthly Curriculum Updates

Agentic AI evolves every week. Our syllabus is updated monthly to reflect the latest framework releases, LLM capabilities, and production patterns.

🤖

Multi-LLM Fluency

You work with GPT-4o, Claude 3.5, Gemini 1.5, and Llama 3 — not locked into one provider. You understand trade-offs and choose intelligently for each task.

🏗️

Production-First Projects

Every project is deployed — not just run in a notebook. You leave with live, accessible URLs to working agent applications you can show in interviews.

🧑‍💻

Practitioners as Instructors

Taught by engineers actively building agentic systems at AI companies. You learn the real-world pitfalls, cost management tricks, and production patterns that no course covers.

🔒

Safety & Guardrails Coverage

Unlike most AI courses, we teach agent safety — prompt injection defence, output validation, cost guardrails, and human-in-the-loop patterns for responsible deployment.

🌐

Exclusive Agent Template Library

Access CodEvo's proprietary library of production-tested agent templates, prompt libraries, and LangGraph workflow blueprints to accelerate your own projects.

🎯

Placement in AI-First Companies

Active connections to AI startups, product companies, and consulting firms specifically seeking Agentic AI engineers — a market segment with far more demand than supply.

🔄

Lifetime Access & Alumni Network

Permanent access to all content, monthly update sessions, and a growing alumni network of Agentic AI practitioners across India and globally.

Your Path from Enquiry to Deployment

From your first conversation with our advisors to your first deployed AI agent — here is exactly how the journey unfolds.

1

Free Counseling

Speak with our advisors to confirm you have the right foundation and understand the program track best suited for you.

2

Enrollment & Setup

Complete admission. Receive API sandbox access, dev environment setup guide, and your first pre-work resources.

3

Live Learning

Progress through 8 modules with weekly live sessions, project builds, code reviews, and framework deep-dives.

4

Build & Deploy

Complete all 8 agent projects. Deploy your capstone agent to production. Publish your GitHub portfolio.

5

Placement Drive

Access AI-first hiring partners, mock interviews with technical panels, and direct referrals to land your role.

Ready to Build AI That Acts?

Join India's Most Advanced Agentic AI Program

Enroll today and become one of the rare engineers who can build, deploy, and ship autonomous AI agents that solve real business problems in production.

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