The Department of Intelligent Computing and Business Systems, in collaboration with the Library & Learning Group, hosted a landmark five-day event from July 27th to 31st, 2026. The week opened with the official inauguration of the Intel Unnati Artificial Intelligence Lab, followed immediately by a Train the Trainer Programme - Faculty Development Program (FDP) focused on hands-on Machine Learning and Deep Learning using Intel’s AI tools and frameworks.
The program began with a traditional ribbon-cutting, invocation, and ceremonial lighting of the lamp. Mr. Govind Agarwala, National Manager, Intel India Pvt Ltd delivered the welcome address, highlighting student-focused initiatives, global competition platforms, and valuable Intel certification paths. Mr. Ravikumar J, Associate Director, Acer India Pvt Ltd, Bangalore shared insights into Acer’s AI infrastructure, calling the new lab a major milestone in preparing engineers for the future. Mr. Harshan P H, Manager of Sales for Karnataka & Kerala, Acer India Pvt Ltd, Bangalore joined the occasion as Guest of Honour. Fr. Wilfred Prakash Dsouza, Director proudly conveyed that our campus is the first college in the district to house an Intel Unnati Lab. He emphasized that this facility will provide students and researchers the tools to look beyond textbooks and tackle complex, real-world problems.
The FDP sessions included a blend of interactive lectures with guided lab sessions. In the initial days participants explored the Intel AI ecosystem, server infrastructure and high-performance computing resources needed to build and deploy modern AI applications. The sessions included key concepts like supervised learning such as linear/logistic regression, gradient descent, regularization, model validation, and unsupervised techniques such as K-means clustering. As the week progressed, participants worked on Convolutional Neural Networks (CNNs) for image classification and with tools like OpenVINO and Intel Extension for PyTorch to understand how trained models can be optimized for faster inference and efficient deployment on Intel hardware. They also gained experience in using AI server environments, OpenPBS and resource management for running AI workloads.
