Agentic AI Meets Adaptive Multi-Agent Systems

The Agentic AI Meets Adaptive Multi-Agent Systems course introduces intelligent agents, agent architectures, adaptive multi-agent systems, and LLM-based agents.

Course Fee - ₹ 2000

Overview

The Agentic AI Meets Adaptive Multi-Agent Systems course introduces intelligent agents, agent architectures, adaptive multi-agent systems, and LLM-based agents. Learners gain practical skills in designing, deploying, and evaluating autonomous AI systems while exploring real-world applications, ethical AI practices, and emerging trends in Agentic AI.

START DATE

Jul 01 2026

END DATE

Nov 30 2026

Delivery Mode

Online

Duration

15 Hours

Type

Theory

Course Fee

₹ 2000

Credentials and Certification

1 Credit
1 Digital Badge
1 Certificate

Course Category Micro-Credential (Advanced)

TARGET AUDIENCE Students, researchers, faculty, AI practitioners, software engineers, data scientists, and industry professionals seeking expertise in Agentic AI, adaptive multi-agent systems, and intelligent autonomous systems.

COURSE DELIVERY

Action-based learning materials with guided assessments and faculty support.

Digital Credential

indicating verified micro-credential completion.

RECOMMENDED FOR

AUDIENCE 01

Students exploring cloud computing

AUDIENCE 02

Professionals planning cloud projects

AUDIENCE 03

Faculty building digital deployment literacy

COURSE DELIVERY

Action-based learning materials with guided assessments and faculty support.

Course Outcomes

Our curriculum matches modern standard practices to provide exceptional training milestones.

Agentic AI Fundamentals

Understand the core concepts of Agentic AI, autonomous systems, and intelligent agents that enable adaptive decision-making in dynamic environments.

CORE KNOWLEDGE

Intelligent Agent Design

Learn to design intelligent agent architectures that perceive, reason, plan, and perform tasks efficiently across diverse real-world applications.

SYSTEM DESIGN

Multi-Agent & LLM Systems

Develop adaptive multi-agent and large language model (LLM)-based systems that collaborate, communicate, and solve complex problems autonomously.

ADVANCED AI

Ethical & Trustworthy AI

Apply ethical AI principles and trustworthy frameworks to ensure transparency, fairness, accountability, and responsible deployment of intelligent systems.

RESPONSIBLE AI

Real-World AI Applications

Explore practical applications of Agentic AI across industries by evaluating autonomous solutions that improve productivity, innovation, and decision-making.

INDUSTRY INSIGHTS

Emerging Trends & Future Opportunities

Evaluate emerging research trends and future opportunities in Agentic AI to prepare for the evolving landscape of autonomous intelligent technologies.

FUTURE READINESS

ELIGIBILITY CRITERIA

Undergraduate students, postgraduate students, researchers, faculty, and industry professionals with basic knowledge of Artificial Intelligence, Machine Learning, or Python programming.

Faculty In Charge

Expert guidance from acclaimed industry professional leaders.

Dr. Rajkumar Rajavel

Assistant Professor

Dr. Rajkumar Rajavel is a researcher and academician with over 15 years of experience in AI and Information Technology. His expertise includes Agentic AI, Multi-Agent Systems, Cloud Computing, Big Data Analytics, and IoT. He has authored 30+ SCI/Scopus publications, holds multiple patents, and actively mentors research in emerging intelligent systems.

Program Overview

Academic Curriculum

A meticulous, guided learning path engineered to transform your cloud engineering expertise.

Module 1

Introduction and Foundations of Agentic AI

Introduction to Agentic AI, Foundations of Intelligent Agents, Key Characteristics of AI Agents

Module 2

Agent Architectures, Decision-Making, and Learning

Architectures and Design Patterns of Agentic AI Systems, Decision-Making and Planning in Agentic AI, Learning in Agentic AI

Module 3

Multi-Agent Systems and LLM-Based Agents

Multi-Agent Systems, Coordination, Cooperation, and Negotiation among Agents, Large Language Models as Agents

Module 4

Agentic AI Frameworks, Interaction, and Responsible AI

Agentic AI Frameworks and Tools, Human–Agent Interaction, Security, Safety, and Ethics in Agentic AI

Module 5

Applications, Advanced Topics, and Future Directions

Agentic AI in Real-World Applications, Advanced Topics in Agentic AI, Future Directions and Open Research Challenges

Agentic AI Meets Adaptive Multi-Agent Systems

Overview

Credentials and Certification

COURSE DELIVERY

Digital Credential

Students exploring cloud computing

Professionals planning cloud projects

Faculty building digital deployment literacy

Course Menu

COURSE DELIVERY

Course Outcomes

Agentic AI Fundamentals

Intelligent Agent Design

Multi-Agent & LLM Systems

Ethical & Trustworthy AI

Real-World AI Applications

Emerging Trends & Future Opportunities

ELIGIBILITY CRITERIA

Faculty In Charge

Dr. Rajkumar Rajavel

Assistant Professor

Academic Curriculum

Introduction and Foundations of Agentic AI

Agent Architectures, Decision-Making, and Learning

Multi-Agent Systems and LLM-Based Agents

Agentic AI Frameworks, Interaction, and Responsible AI

Applications, Advanced Topics, and Future Directions

Build skills that matter in the real world