Presidency School of Computer Science & Engineering (PSOCSE) organised a five-day Faculty Development Programme (FDP) on “Machine Learning Techniques” from 21 to 25 July 2026, from 9:00 am to 4:15 pm at LFL01. The programme was convened by Dr Pallavi R and coordinated by Ms Shet Reshma Prakash and Ms Prachi Amol Gadhikar, with 51 faculty members registered. The FDP aimed to strengthen participants’ conceptual and practical understanding of Machine Learning and Artificial Intelligence, while enhancing teaching competencies, research capabilities and industry-oriented curriculum development.

The programme featured sessions by distinguished academic and industry experts, including Mr Bhavya Verma, Scientist, CMTI, Bengaluru; Dr Deepti Sisodhia, Associate Professor, MIT, Bengaluru; Dr Swati Sharma, Dr Anand Prakash, Dr Sandeep Albert Mathias, Dr Bhuvaneshwari Patil, Dr Megala G and Dr Sivaramakrishnan S from Presidency University, Bengaluru. Key topics included Machine Learning fundamentals and industrial applications, the transition from classical Machine Learning to Deep Learning for industrial vision inspection, supervised and unsupervised learning, ensemble learning, model evaluation metrics, quantum Machine Learning, imbalanced learning and data balancing techniques. A hands-on session on credit card fraud detection using Google Colab provided participants with practical exposure to real-world Machine Learning applications.

The FDP enhanced participants’ understanding of both foundational and advanced Machine Learning techniques and enabled them to apply these concepts through practical exercises and problem-solving activities. The programme encouraged knowledge sharing and collaboration among faculty members, researchers and industry experts, while highlighting opportunities for interdisciplinary research and curriculum enhancement. The learning outcomes are expected to support improved teaching practices, industry-relevant course development, research in AI and Machine Learning, and future academic and industry collaborations.