The Department of Artificial Intelligence and Data Science organized an online workshop titled “From Data to Autonomy: The Agentic AI Revolution – Principles, Protocols and Practice” on 16th October 2025. The session was conducted by Mr. J. Balamurugan, who shared his expertise on Artificial Intelligence (AI), Machine Learning (ML), and emerging Agentic AI systems. The workshop aimed to enhance participants’ understanding of data-driven intelligence, autonomous systems, and AI protocols that govern modern intelligent technologies.
The workshop provided valuable insights into the following key areas:
Introduction to Data and Big Data:
Participants gained an understanding of the fundamental concepts of data, its types, and the significance of Big Data in today’s digital world. The session highlighted how massive datasets are generated, stored, and analyzed to drive innovation and data-informed decision-making.
Introduction to Artificial Intelligence:
The trainer introduced the core principles of Artificial Intelligence, its evolution, and its transformative impact across various sectors such as healthcare, finance, and education.
Concepts of Machine Learning Algorithms:
An overview of different Machine Learning techniques, including supervised and unsupervised learning, was presented. The session also explored their real-world applications in pattern recognition and predictive analytics.
Concepts of Deep Learning Methods:
Participants explored the fundamentals of Deep Learning, focusing on neural network architectures and their roles in advanced AI systems such as image and speech recognition.
Classification of AI Agents and Agentic AI:
The workshop explained the various types of AI agents, their characteristics, and the emerging concept of Agentic AI. Emphasis was placed on how intelligent agents perceive their environment and act autonomously to achieve defined goals.
Agentic AI Protocols:
The session concluded with an overview of the emerging protocols and frameworks guiding the functioning, communication, and coordination of Agentic AI systems. The discussion highlighted the importance of safety, reliability, and interoperability in multi-agent environments.
The workshop was highly informative and engaging, enabling participants to gain in-depth knowledge of evolving AI technologies and their applications in achieving autonomous and intelligent system design.
