Event Title: Bridging the Futures: Data Science, Machine Learning, and Research pathway

Date: 16-07-2025 to 18-07-2025

Time: 12:30 pm to 5:40 pm

Venue: Room no: 507

Organizing Head: Dr S. Thirumagan, Dean – FSH

Advisor: Dr.J.Dhilipan (VP Admin)

HOD: Dr. N. Vijayalakshmi, Associate Professor & HOD

Event Convenors: Dr.S.Karthiga, Dr.S.Saradha, Dr.Gayathri, Mr.D.B.Shanmugam

No. of Participants: 110 participants

Summary of the Event:

The Department of Computer Science and Applications (DS)

  • Organized “Bridging the Futures: Data Science, Machine Learning, and Research pathway”. On 16-07-2025 to 17-07-2025
  • N. Vijayalakshmi, Associate Professor & HOD – Faculty members emphasized the importance of aligning academic knowledge with industry needs. They discussed how practical skills and real-world applications can enhance student readiness for professional careers.
  • S. Saradha, Associate Professor – The session introduced students to NLP concepts such as text analysis and language understanding. Real-world applications like chatbots and sentiment analysis were also highlighted.
  • Renuka Devi, Assistant Professor – Students were briefed on the fundamentals of machine learning, including types of learning and model training. The importance of data-driven decision-making was emphasized through practical examples.
  • R. Ramya Devi, Assistant Professor – This session covered the basics of data warehousing and big data technologies. Tools and concepts used in large-scale data processing and storage were briefly introduced.

Outcome of the Event Based on SDG:

This event achieved remarkable outcomes, supporting multiple Sustainable Development Goals (SDGs).

SDG 4 (Bridge gap between Academic and Research): The course emphasized the need to align academic learning with real-world industrial demands. Sessions focused on exposing students to current trends and practical applications in data science, helping them connect theoretical knowledge with industry practices. By showcasing real-time case studies and practical scenarios, the program helped reduce the disconnect often faced by students entering the workforce.

SDG 4 (Introduction to Natural Language Processing): Students were introduced to the basics of Natural Language Processing, a branch of AI that focuses on the interaction between computers and human languages. The session included insights into text analysis, sentiment detection, and language modeling. Participants learned how NLP is powering applications like chatbots, voice assistants, and language translators in today’s digital world.

SDG 4 (Introduction to Machine Learning): This module provided students with a conceptual overview of Machine Learning, highlighting types such as supervised, unsupervised, and reinforcement learning. Real-world applications—like recommendation systems, fraud detection, and image recognition—were discussed. The session helped students understand the process of building and training ML models and the importance of data in making predictions.

SDG 4 (Introduction to DataWare house and Big Data): The course also introduced Data Warehousing and Big Data Technologies, stressing the need to manage and process massive datasets efficiently. Students learned the difference between traditional databases and data warehouses and were introduced to tools like Hadoop and Spark. The session emphasized how big data analytics helps organizations gain insights and drive business decisions.