Faculty Development — Courses, Training and Resources
This page provides Faculty Development resources for teachers and faculty members in Computer Science and related areas. The material is intended to support teaching, curriculum development, academic preparation, and continuing professional development.
The resources include lecture materials, tutorials, course content, and other academic resources that may assist faculty members in updating their knowledge and strengthening their teaching practices.
Faculty Development Program: 2026–27
FDP on Research Excellence in AI Era: Latex for Research Documentation and Publication
Five-Day Online Faculty Development Programme (FDP) on “Research Excellence in AI Era”, was organized by the Department of Electrical Engineering, JIET, Jodhpur, from August 24 to 29, 2026. One of the area of deliberation was application of Latex Tools for research documentation and publication.
Faculty Development Program: 2025–26
FDP on Data Science: Deep Learning and AI
This faculty development session was delivered at the Department of Computer Science and Engineering, MBM University during the PM-USHA sponsored FDP on Data Science (23–30 March 2026). The lecture focused on Generative AI and Large Language Models, discussing their foundations, applications, and implications for teaching, research, and industry.
FDP on Image Processing and Computer Vision
These sessions were conducted at the Department of Computer Science and Engineering, MBM University under the PM-USHA sponsored FDP on "Image Processing and Computer Vision” (7–12 July 2025). The lecture presented a comprehensive overview of machine learning, tracing its evolution from basic neural networks to modern deep learning architectures.
Deep Learning and Visual AI
Faculty Development Program: 2023-24
FDP topic: Generative AI
This program explored Generative AI: Opportunities and Challenges, providing insights into emerging AI technologies and their applications in education and research. It also addressed practical challenges, ethical considerations, and strategies for integrating generative AI into academic environments.