Agentic AI Program

Agentic AI is a live, instructor-led program designed to build strong skills in autonomous AI systems, intelligent agents, and AI application development using modern generative AI and agent frameworks.

  • This 24-week structured journey includes real AI agent development projects, 10+ hands-on workshops, 30+ real-world AI automation use cases, and masterclasses with continuous mentorship.
  • You will work with industry tools such as Python, LLM APIs, LangChain, vector databases, prompt engineering frameworks, and agent orchestration tools.
  • The program also provides an option to pursue industry-recognized certifications including Microsoft Azure AI Engineer Associate, Google Generative AI Certification, AWS Machine Learning Specialty, and OpenAI Developer credentials.
Format Live Instructor-Led
Duration 24 Weeks | 180 Hours
Prerequisites Foundations in AI/ML or Data Science, with experience in Python, machine learning basics, and working with APIs
Admission Deadline 30 April 2026
Case Studies & Projects 30+
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Key Program Takeaways

Build real Agentic AI capability through guided labs, autonomous agent workflows, and project-based learning designed for intelligent automation and AI-powered applications.

LLM Foundations

Prompt Engineering, Model Interaction, AI Capabilities

Agent Frameworks

LangChain, Agent Workflows, Tool Integration

Data & Knowledge Retrieval

Vector Databases, Embeddings, Retrieval-Augmented Generation

Autonomous Workflows

Planning, Multi-Step Reasoning, Task Automation

AI Application Development

API Integration, AI Assistants, Intelligent Automation

Capstone Portfolio

End-to-End AI Agent Application Deployment

List of Modules in this Program

01

Foundations of Agentic AI

  • Introduction to generative AI, large language models, and intelligent agents.
  • Understand how AI agents reason, plan, and execute tasks.
  • Overview of agent architectures and real-world AI automation systems.
02

Python for AI Applications

  • Use Python to build AI-driven applications and workflows.
  • Work with APIs and SDKs for integrating AI models into applications.
  • Process data and build scripts that interact with AI systems.
03

Prompt Engineering & LLM Interaction

  • Learn effective prompt design and optimization techniques.
  • Control model outputs through structured prompts and system instructions.
  • Build prompt pipelines for complex AI tasks.
04

Agent Frameworks & Tool Integration

  • Build autonomous agents using LangChain and orchestration tools.
  • Integrate external tools, APIs, and databases with AI agents.
  • Design multi-step reasoning workflows and tool-using agents.
05

Knowledge Retrieval & AI Systems

  • Implement vector databases and embedding-based search.
  • Build retrieval-augmented generation (RAG) pipelines.
  • Enable AI agents to access and reason over knowledge bases.
06

Capstone Project

  • Design and build an end-to-end AI agent application.
  • Integrate LLMs, tools, and knowledge retrieval systems.
  • Deploy a portfolio-ready Agentic AI solution that automates real workflows.

Hands-On Roadmap

Weeks 1–4

Generative AI Foundations & Environment Setup

  • Install Python and AI development tools
  • Work with LLM APIs and experiment with model interactions
  • Understand prompt structures and response control
  • Hands-on: Prompt Playground Tool, AI Text Analysis Assistant
Weeks 5–8

Prompt Engineering & LLM Workflows

  • Design advanced prompts and structured AI interactions
  • Build prompt pipelines for multi-step tasks
  • Integrate LLM APIs into simple applications
  • Hands-on: AI Content Generator, Automated Research Assistant
Weeks 9–12

Building AI Agents

  • Build agent workflows using LangChain and similar frameworks
  • Implement tool-using agents that interact with APIs
  • Design multi-step reasoning pipelines
  • Hands-on: AI Web Research Agent, Data Insights Agent
Weeks 13–16

Retrieval-Augmented AI Systems

  • Implement vector databases and embeddings
  • Build retrieval-augmented generation (RAG) pipelines
  • Connect agents to knowledge bases and document sources
  • Hands-on: AI Knowledge Base Assistant, Document Q&A System
Weeks 17–20

Multi-Agent Systems & AI Automation

  • Build multi-agent orchestration workflows
  • Integrate external APIs and enterprise tools
  • Automate complex workflows using AI agents
  • Hands-on: AI Workflow Automation System, Intelligent Task Manager
Weeks 21–24

Capstone Agentic AI Project

Build a production-ready AI agent capable of solving real-world tasks.
  • Design full agent architecture and workflows
  • Integrate LLMs, tools, and knowledge retrieval systems
  • Deploy and demonstrate AI automation solutions
  • Capstone project options:
  • Autonomous Business Research Agent
  • AI Customer Support Automation System
  • Enterprise Knowledge Assistant

Top Companies Hiring Agentic AI & Generative AI Engineers

Leading technology companies, AI labs, startups, and digital platforms actively hire engineers to build AI agents and intelligent automation systems.

OpenAI Google Microsoft Meta Amazon Apple NVIDIA Anthropic Tesla IBM Oracle Salesforce McKinsey & Company BCG Bain & Company Deloitte Accenture Goldman Sachs JPMorgan Chase Morgan Stanley Flipkart Paytm Razorpay Swiggy Zomato PhonePe Infosys TCS Wipro Cognizant

Some of our exceptional outcomes with top companies.

Sai Arya

Sai Arya

₹65 LPA CTC

Nitish

Nitish

₹65 LPA CTC

Manurbhav A

Manurbhav A

₹21 LPA CTC

Aditya T

Aditya T

₹21 LPA CTC

Om Nakrani

Om Nakrani

₹65 LPA CTC

Yuvana T

Yuvana T

₹22 LPA CTC

Pardhiv A

Pardhiv A

₹21 LPA CTC

Phanindra B

Phanindra B

₹19 LPA CTC

Sai Gokul

Sai Gokul

₹65 LPA CTC

Abhigyan N

Abhigyan N

₹65 LPA CTC

Aryan T

Aryan T

₹21 LPA CTC

Devendra A

Devendra A

₹65 LPA CTC

Mahesh Reddy

Mahesh Reddy

₹65 LPA CTC

Prakul K

Prakul K

₹21 LPA CTC

Prashanth Reddy K

Prashanth K

₹65 LPA CTC

Rajeev T

Rajeev T

₹21 LPA CTC

Master Technologies

Core generative AI, agent frameworks, LLM tooling, and AI infrastructure technologies used throughout the program.

Python logoPython
OpenAI API
LangChain logoLangChain
LlamaIndex
Hugging Face logoHugging Face
Vector Databases (Pinecone / Weaviate / FAISS)
Prompt Engineering Frameworks
Retrieval-Augmented Generation (RAG)
Embeddings & Semantic Search
FastAPI logoFastAPI
Docker logoDocker
Git logoGit & GitHub
AWS AI Services
Azure OpenAI
Google Vertex AI logoGoogle Vertex AI
Streamlit logoStreamlit / Gradio

Eligibility & Admission

A fully online, straightforward admissions process with advisor support throughout enrollment.

Who Can Apply Eligibility requirements for enrollment
  • Graduates in computer science, IT, data science, engineering, or related disciplines.
  • Final-year undergraduate students completing their degree before the program concludes.
  • Professionals with foundations in AI/ML or data science and working Python/API knowledge.
Admission Process Simple, structured steps from application to enrollment
  1. Application Submission: Complete a short online application with academic/professional details.
  2. Profile Review: Selected applicants receive official admission confirmation.
  3. Seat Confirmation: Reserve your seat with INR 10,000.
  4. Fee Completion: Pay the remaining fee within 7 days of confirmation or before program start, whichever is earlier.
Learner Assistance Advisor support throughout your admission journey

Program advisors are available 7 days a week, 10:00 AM to 7:00 PM.

Email: hello@42learn.com

Phone: 080 4736 3406

Disclaimer: Outcome, career progression, and salary information is indicative only; individual results vary by background, experience, and market conditions. Certificates/credits are governed by the issuing institution's policies where external partners are involved.