AI Agent Engineering

Learn the Skills Powering the Next Generation of Intelligent Applications

Artificial Intelligence is rapidly transforming the way software is built, deployed, and used. Modern AI systems are no longer limited to answering questions or generating content. They can reason, plan tasks, use tools, access knowledge bases, communicate with other agents, and perform complex workflows with minimal human intervention.

The AI Agent Engineering Master Series is a comprehensive learning program designed for B.Tech, MCA, M.Tech students, and working professionals who want to build a strong foundation in modern AI engineering and agent development.

This series takes learners from the fundamentals of Generative AI to advanced concepts such as Retrieval-Augmented Generation (RAG), AI Agents, Multi-Agent Systems, Model Context Protocol (MCP), and Production AI deployment.

Whether your goal is placement preparation, academic learning, research, or industry upskilling, this series provides both conceptual understanding and practical implementation experience.

Who Should Join?

  • B.Tech (CSE, IT, AI, Data Science) Students

  • MCA Students

  • M.Tech Students

  • Software Engineers

  • AI/ML Enthusiasts

  • Backend Developers

  • Solution Architects

  • Technical Leads

What You Will Learn

Module 1: AI Foundations

  • Introduction to Generative AI

  • Understanding Large Language Models

  • Prompt Engineering

  • AI Application Architecture

  • OpenAI, Claude, and Gemini Overview

Module 2: RAG Engineering

  • Retrieval-Augmented Generation

  • Embeddings

  • Vector Databases

  • Semantic Search

  • PDF Chatbots

  • Hybrid Search

  • RAG Evaluation

Module 3: AI Agent Fundamentals

  • AI Agents

  • Agent Lifecycle

  • Tool Calling

  • Memory Management

  • Planning and Reasoning

  • Reflection Patterns

  • Autonomous Agents

Module 4: Agent Frameworks

  • LangGraph

  • CrewAI

  • AutoGen

  • Semantic Kernel

  • OpenAI Agents SDK

Module 5: Model Context Protocol (MCP)

  • MCP Fundamentals

  • MCP Architecture

  • MCP Servers

  • MCP Clients

  • Database MCP

  • File System MCP

  • Enterprise MCP Design

Module 6: Multi-Agent Systems

  • Agent Communication

  • Agent Orchestration

  • Supervisor Agents

  • Research Agents

  • Coding Agents

  • Customer Support Agents

Module 7: Production AI

  • Agent Security

  • AI Observability

  • Evaluation Frameworks

  • Cost Optimization

  • Monitoring Agent Workflows

  • Human-in-the-Loop AI

Module 8: Capstone Projects

  • AI Career Counselor

  • AI Placement Assistant

  • AI Coding Mentor

  • AI Research Assistant

  • AI Interview Coach

  • AI University Helpdesk

  • Multi-Agent Campus Assistant

What Makes This Series Different?

  • Simple and easy-to-understand explanations

  • Real-world examples from industry

  • Placement-focused interview preparation

  • Hands-on module projects

  • Enterprise architecture discussions

  • .NET and Python implementation examples

  • Step-by-step learning path

  • Industry-ready capstone projects

Skills You Will Gain

  • Generative AI Development

  • Prompt Engineering

  • RAG Development

  • Vector Database Integration

  • AI Agent Development

  • Multi-Agent Architecture Design

  • MCP Development

  • AI System Deployment

  • AI Monitoring and Optimization

  • Enterprise AI Solution Design

Final Outcome

By completing this Master Series, learners will be capable of designing, developing, deploying, and managing intelligent AI systems that can solve real-world business and academic challenges. They will gain the knowledge required for placements, internships, higher studies, and professional AI engineering roles.