Short Term Course #1
Introduction to Data Science with Practice Problems and Project Ideas
This one-year (extendable) self-paced Data Science certificate course covers performance metrics, statistical analysis, MCDM, Artificial Neural Networks, and conventional and nature-inspired optimization techniques, all taught with real-life case studies and example problems. Learners work through topics such as outlier and trend detection, correlation, risk and uncertainty, regression, ANN modeling and training, MCDM methods (AHP, ANP, MAUT, EVAMIX, ELECTRE, PROMETHEE), and optimization methods (Linear/Dynamic/Quadratic Programming, PSO, ACO, GA, Glowworm, Firefly, Mine Burst). Weekly online assignments and monthly tests support continuous learning, and on successful completion, participants receive a certificate, emailed materials for long-term use, ongoing updates while subscribed, and scope for publication based on high-quality work.
Short Term Course #2
Introduction to Remote Sensing and Geographic Information Systems (GIS)
Remote sensing is the process of gathering information about objects or phenomena without physical contact, while GIS (Geographic Information System) captures, stores, and analyzes spatial data; together, they enable effective data-driven decision-making across sectors like agriculture, urban planning, environment, and resource management. This self-paced certificate course teaches concepts and techniques of remote sensing, GIS, GPS, and image processing—including map digitization, shapefile creation, satellite imagery analysis, and geodatabase and GeoApps development—to empower learners with the skills needed for sustainable city planning and research applications. The one-year program offers videos, quizzes, graded assignments, and one-to-one mentorship, with opportunities for certification and publication, particularly benefitting students and professionals in science and engineering fields interested in spatial data analysis and technological applications.
Short Term Course #3
Introduction to Artificial Intelligence with Project Ideas and Practice Problems
This self-paced certificate course introduces Artificial Neural Networks (ANN), the backbone of Artificial Intelligence, covering both simple and polynomial neural networks through self-explanatory presentations and example problems. Learners study ANN fundamentals, parameter estimation, training and testing, validation, and advanced training algorithms such as Quick Propagation, Conjugate Gradient Descent, Newton’s Method, Quasi-Newton, and Levenberg–Marquardt, along with performance evaluation using error, correlation, and efficiency metrics and case studies, including applications in water resources development. The course uses no-code ANN software, runs for a minimum of one year, includes videos, readings, practice quizzes, graded assignments and quizzes with feedback, one-to-one interaction with the coordinator, and offers a certificate of completion plus opportunities for paper or book chapter publication upon successfully passing assignments and tests.
Short Term Course #4
Introduction to Optimization Technique with Practice Problems and Project Ideas
This self-paced course offers a brief yet structured introduction to optimization techniques, covering both conventional and nature-inspired methods through self-explanatory presentations and example problems. Learners explore core topics such as the concept of optimization, differences between simulation, prediction and optimization, classification of optimization techniques, and specific methods including Particle Swarm Optimization, Artificial Neural Networks, Polynomial Neural Networks, Ant Colony Optimization, Linear Programming, and Dynamic Programming. Weekly assignments and end-of-month tests are included to reinforce learning, and upon successfully clearing the tests, participants receive a Certificate of Completion and are offered a scope for publication.
Short Term Course #5
Introduction to Multi-Criteria Decision-Making Making Techniques with Practice Numericals and Project Ideas
This self-paced one-year certificate course on Multi-Criteria Decision Making (MCDM), coordinated by Dr. Mrinmoy Majumder, covers the fundamentals of MCDM, classification of techniques, and their basic working principles, followed by detailed compensatory methods such as Analytical Hierarchy Process, Analytical Network Process, Weighted Sum Method, Weighted Product Method, and EVAMIX, as well as outranking techniques including ELECTRE and PROMETHEE, with every technique explained through examples and supported by practice problems. Participants receive a certificate upon completion, enjoy scope for paper or book chapter publication, and have the opportunity for one-to-one interaction with the coordinator for the entire year.
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