Online Course on
Advanced Choice Modelling Methods with Applications in Transportation and Urban Systems
The course introduces advanced discrete choice modelling techniques for analyzing travel behavior and decision-making.
Course at a Glance
Know the Course Instructor
Abdul Rawoof Pinjari
He is a Professor in the Centre for Infrastructure, Sustainable Transportation and Urban Planning (CiSTUP) at the Indian Institute of Science (IISc). His research focuses on advanced choice modelling, travel demand forecasting, transportation planning, and urban systems, with applications in sustainable mobility and data-driven transportation policy.
Objectives of the Course
Covers the theory and advanced methods of choice modelling, with applications drawn from travel behaviour analysis in emerging urban settings with new modes such as shared mobility, ride hailing, integrated multimodal transit, and electric vehicles.
Assumes familiarity with the basic choice modelling methods such as the multinomial logit and maximum likelihood estimation.
Quickly delves into advanced model formulations and estimation methods.
Gives equal emphasis to empirical model specification and behavioural interpretation issues, including causality and behavioural heterogeneity.
Covers the importance of hands-on estimation, specification, and interpretation of choice models on real-life empirical datasets.
Includes a mix of PowerPoint presentations and chalk-and-board sessions.
Accompanies lectures with software laboratory sessions to provide hands-on experience with model formulations and estimation methods.
Provides open-source codes written in Python and other statistical packages for the software sessions.
Course Syllabus
Brief review of utility-based choice theories, multinomial logit, and maximum likelihood estimation
Mixed logit and multinomial probit models, models with stochastic variables
Multivariate dependent variable models (e.g., multivariate ordered response models)
Parameter identification in basic and advanced choice models
Discrete-continuous choice models and multiple discrete-continuous choice models (MDCEV, etc.)
Advanced estimation methods
Modelling lab sessions with estimation, specification, behavioural interpretation, and application exercises
Who Can Apply & Who Can Benefit?
Who Can Apply?
- BTech, MTech, BSc, MSc, BA, BCom, BStats., BBA, MBA
- Calculus, Applied Probability and Statistics, Matrix Algebra
Who Can Benefit?
- Students and researchers interested in transportation planning, urban systems, travel behaviour analysis, and data-driven decision-making.
- Professionals, consultants, and policymakers working in transportation, mobility, urban planning, and infrastructure sectors seeking advanced choice modelling skills.
Class Schedule
Fee Structure
| Category | Fee |
|---|---|
| Students | ₹8,500 + GST |
| Academic Institutions & R&D Units (Non-students) | ₹18,000 + GST |
| Industry Participants | ₹25,000 + GST |
| Participants from Institutions outside India | ₹45,000 + GST |
Ready to Enroll?
Apply online at iisc.online · New batches every semester