On February 3, 2026, Srinivas Institute of Technology conducted Day 2 of the AI research bootcamp titled “GENAIVATION 2026: Innovation to Publication.” The program was organized in association with DHAARINI an AI-Tech Research Academy, with the joint effort of the ISE, CSD, and AI-DS departments.

Day 2 of the AI research bootcamp focused on model evaluation techniques and effective AI prompting methods. The session was conducted by Mr. Prashanth Kannadaguli, Trainer. The aim of the session was to help students understand how machine learning models are evaluated and improved.

The session began with an explanation of k-fold cross validation, helping students understand how data is divided to test models more reliably. Concepts such as underfitting, overfitting, and good fit were discussed to explain correct model behavior.

The trainer explained types of model evaluation methods used in machine learning. Important classification metrics such as accuracy, precision, and recall were explained with simple examples. Regression metrics were also introduced to show how prediction errors are measured.

The session also covered effective AI prompting techniques, including text prompting, chain-of-thought, and tree-of-thought approaches. Students were introduced to the four essential domains and an interview pattern approach, helping them understand how these topics are used in technical interviews.

The program received strong support from Dr. Shrinivasa Mayya D, Principal of Srinivas Institute of Technology. The guidance of Prof. Sudarshan K, Head of the Department, ISE & CSD, and Prof. Nagaraja Hebbar, Head of the Department, AI-DS, played an important role in the smooth conduct of the program. The event was also supported by Dr. Praveen Shenoy, IIC Coordinator, and Prof. Rakesh Mallya. Additional support was provided by Prof. Archana D, ACODE Advisor, Prof. Ajay Pinto, AADE Advisor, and Prof. Sowmya, AISE Advisor. The program was successfully coordinated by Prof. Aparna N, Prof. Sahana B, and Prof. Ganapathi Sharma.

Overall, Day 2 was informative and practical, strengthening students’ understanding of evaluation methods and AI-based problem solving.