Databricks and Agentic AI introductory Workshop

Workshop Report Databricks and Agentic AI – Introductory Workshop

Introduction

The Department of Information Science and Engineering organized an introductory workshop on “Databricks and Agentic AI” to familiarize students with the latest developments in data engineering and artificial intelligence. The session was conducted by an AQMATICS Industry Expert and focused on bridging the gap between traditional data engineering practices and the rapidly evolving AI ecosystem.

The workshop introduced participants to modern Lakehouse Architecture, the Databricks platform, and the emerging concept of Agentic AI, enabling students to understand how intelligent autonomous systems are transforming enterprise data processing and business automation.

Topics Covered

Session Highlights

The workshop was structured around two major themes:

1. Databricks – The Modern Lakehouse

The speaker explained how the Databricks Lakehouse Platform simplifies enterprise data engineering by providing a unified environment for data storage, analytics, and artificial intelligence. Students learned how Databricks eliminates the complexity of managing multiple cloud services and enables organizations to build scalable data solutions using a single platform.

Live demonstrations showcased important features such as Workspace, Serverless SQL, and Genie, illustrating how natural language queries can simplify business intelligence and data analytics.

2. Agentic AI

The second part of the workshop introduced the concept of Agentic AI, where autonomous AI agents perform reasoning, planning, and execution of complex business tasks beyond traditional Large Language Models (LLMs).

The speaker demonstrated how Agent Bricks interact with enterprise data to automate workflows, improve decision-making, and support intelligent business operations. The discussion also highlighted the growing importance of Agentic AI across industries and its role in next-generation enterprise applications.

Session Schedule

Student Participation

The workshop witnessed active participation from 6th Semester students of the Information Science and Engineering Department, along with faculty members. Student registration was coordinated through an official Google Form, enabling efficient attendance management and event communication.

The registration process collected the following information:

• Student Name
• Institutional Email ID
• Department
• Year of Study
• Contact Number

The collected information was used exclusively for workshop coordination and post-event communication in accordance with institutional data privacy practices.

Infrastructure and Technical Support

The programme was conducted in the institute auditorium equipped with modern teaching facilities.

Key Learning Outcomes

At the end of the workshop, participants were able to:

• Understand the architecture and advantages of the Databricks Lakehouse Platform.
• Explain the concept of unified data engineering and modern analytics platforms.
• Differentiate between traditional AI models and Agentic AI systems.
• Understand the role of autonomous AI agents in enterprise automation.
• Gain awareness of industry-recognized Databricks certifications and AI career opportunities.
• Identify emerging career paths in Data Engineering, AI Infrastructure, and Intelligent Enterprise Systems.

Conclusion

The Databricks and Agentic AI – Introductory Workshop was an informative and industry-focused programme that successfully introduced students to the latest trends in data engineering and artificial intelligence. The session combined conceptual learning with live platform demonstrations, enabling participants to understand the practical applications of Databricks and Agentic AI in modern enterprises.

The interaction with the industry expert provided valuable insights into current technology trends, certification opportunities, and career pathways in AI Infrastructure and Data Engineering. The workshop served as an important initiative in aligning the academic curriculum with the rapidly evolving demands of the technology industry and encouraged students to pursue advanced learning in data and AI technologies.