Build Intelligent AI Agents That Think, Plan, and Execute — From Foundations to Production
Instructor: Dr. Ananjan Maiti | AI Researcher & Educator | 11+ Years in AI/ML Research
The AI industry is undergoing its most significant transformation since deep learning. We are moving beyond chatbots and content generators into the era of Agentic AI — intelligent systems that autonomously plan tasks, make decisions, use external tools, and execute complex workflows with minimal human intervention. Organizations worldwide are racing to adopt agentic architectures, and the demand for professionals who can design, build, and deploy AI agents has never been higher.
This comprehensive course takes you from the foundational principles of agentic AI through advanced production-ready architectures. Whether you are a developer, researcher, data scientist, or technology leader, this course equips you with the knowledge and practical skills to build AI agents that solve real-world problems.
What You Will Learn
This course covers the complete agentic AI stack through four carefully structured modules, each building upon the previous one. You will understand the theoretical foundations, master the leading frameworks and tools, implement advanced retrieval and memory systems, and deploy production-grade AI agents with proper guardrails and evaluation pipelines.
- Agentic AI Foundations — Understand what separates agentic systems from traditional AI and generative models
- Frameworks and Tools — Master LangChain, LangGraph, CrewAI, AutoGen, and no-code platforms
- RAG, Memory, and Planning — Build retrieval-augmented generation pipelines, implement persistent memory, and design planning architectures
- Production Deployment — Ship AI agents with Model Context Protocol, guardrails, evaluation frameworks, and enterprise-grade safety
Course Modules
Module 1: Foundations of Agentic AI
Understand the evolution from traditional AI to large language models to agentic systems. Learn the core concepts of autonomy, goal-driven behavior, planning, memory, tool use, and the agentic loop. Explore the React pattern, chain-of-thought reasoning, and how modern AI agents decompose complex problems into executable steps.
Module 2: Frameworks and Tools for Building AI Agents
Dive deep into the leading agentic AI frameworks — LangChain for composable chains, LangGraph for stateful multi-step workflows, CrewAI for multi-agent collaboration, and AutoGen for conversational agent teams. Explore no-code solutions like n8n for rapid prototyping. Compare frameworks to choose the right tool for every use case.
Module 3: RAG, Memory Systems, and Advanced Architectures
Master Retrieval-Augmented Generation from basic vector search to agentic RAG with dynamic retrieval strategies. Implement short-term and long-term memory systems. Learn planning architectures including task decomposition, self-reflection, and iterative refinement. Explore vectorless RAG approaches and hybrid retrieval methods.
Module 4: Production-Ready AI Agents
Deploy AI agents in production environments with the Model Context Protocol for tool integration, implement guardrails for safety and compliance, build evaluation pipelines to measure agent performance, and design enterprise-grade architectures with monitoring, logging, and human-in-the-loop oversight.
Who Is This Course For?
- Software Developers looking to build intelligent automation systems
- Data Scientists and ML Engineers expanding into agentic architectures
- Technical Leaders and Architects designing enterprise AI strategies
- Researchers and Academics exploring the frontiers of autonomous AI
- Entrepreneurs and Consultants building AI-powered products and services
- Students and Career Changers entering the AI industry with production-relevant skills
Prerequisites
Basic familiarity with Python programming and a conceptual understanding of large language models is recommended. No prior experience with AI agents or specific frameworks is required — the course starts from first principles and builds progressively to advanced topics.
Why Learn Agentic AI Now?
The global agentic AI market is projected to exceed $100 billion within the next decade. Companies across every sector — healthcare, finance, legal, education, cybersecurity, and operations — are actively seeking professionals who can design and deploy AI agent systems. Early expertise in this rapidly evolving field positions you at the forefront of the most transformative technology shift since the internet.
Unlike traditional AI skills that focus on model training and fine-tuning, agentic AI skills are immediately applicable to business automation, workflow optimization, and intelligent system design. The professionals who master these skills today will lead the AI-powered organizations of tomorrow.
About the Instructor
Dr. Ananjan Maiti brings over 11 years of research experience in artificial intelligence, deep learning, and computer vision. With published research in leading international journals, patents in AI innovation, and extensive teaching experience, Dr. Maiti combines rigorous academic depth with practical industry perspective. His research spans neural network architectures, intelligent systems, and applied AI — providing students with insights that bridge theory and production reality.
Frequently Asked Questions
How long does the course take to complete?
The course is designed to be completed in 4 to 6 weeks with approximately 5 to 8 hours of study per week. Each module includes reading material, practical exercises, and project work. Self-paced learners can progress faster or take additional time as needed.
Do I need expensive hardware or cloud resources?
Most exercises can be completed using free-tier cloud services and open-source models. The course emphasizes practical approaches that work within typical resource constraints, with guidance on scaling when needed for production deployments.
Will I build real AI agents during the course?
Yes. Each module includes hands-on projects where you build functional AI agents — from simple conversational agents to multi-agent systems with memory, tool use, and retrieval capabilities. By the end of the course, you will have a portfolio of working AI agent implementations.
Is this course suitable for non-programmers?
Module 2 covers no-code platforms like n8n that enable building AI agents without programming. However, for the full depth of the course, basic Python knowledge is recommended. The course includes resources for building foundational programming skills if needed.
How is this different from other AI courses?
Most AI courses focus on model training or prompt engineering. This course specifically addresses the emerging field of agentic AI — teaching you to build systems that autonomously plan, decide, and execute. The curriculum reflects the latest industry developments including MCP, agentic RAG, multi-agent collaboration, and production guardrails that are rarely covered elsewhere.