CS-302 Modeling and Simulation
(CS-302 Modeling and Simulation)

Course Placement

Modeling and Simulation is a core course offered to third year students of B.Tech Hons. ICT (Minor in Computational Science) program. It is a pre-requisite for domain based specialization electives such as Computational Finance, Computational and systems Biology and Computational Physics.

Course format

  • 3 hours of lecture per week.

  • 3 hours lab per week.


Introductory Calculus, Probability and Statistics, Introductory Physics and Numerical methods. Some experience with scientific computing would be beneficial but is not required.

Course Content

This course introduces students to fundamentals of creating mathematical models of physical systems and implementation on computers to analyze the system both to gain insight and make predictions. The different mathematical approaches to modelling that are covered in the course can be characterized into differential and difference equation based models, probability based models which includes stochastic differential equations, cellular automata and event based approaches, and matrix based models. The course is interdisciplinary in nature and looks at many systems from physics, biology, finance, engineering etc. from a modeling perspective. Each topic is followed by many examples from different disciplines. The students test and create models of these systems in the lab and report on it following the complete modelling approach.

Approach to be followed

system → Analyze the problem (determine problem's objective)→Formulate model (Gather data, make assumptions, determine equations/functions) → Solve model (Computer implementation) →Verify and interpret solutions → make predictions.

Text Book

  • Angela B. Shiflet & George W. Shiflet. Introduction to Computational Science: Modeling and Simulation for the Sciences. Princeton University Press, 2006.

Assessment method/Grading

Written exam: Two mid-semester examinations and a final exam/project: 70% (20+20+30)

Lab207: Lab Assignment, Viva, report submission: 30%

Course Outcome

After successful completion of the course the students would be able to create a relevant model for a multitude of problems from science and engineering, by extracting the necessary and relevent information regarding the problem. They would also be able to define the different modeling terms by analyzing the system or the data that is present. They would be able to implement the model on the computer and from the results check for the validity of the model and correcness of the assumptions present in the model. The should be able to analyze the outcomes (mostly through visualizations) and make predictions. They would also be able to understand the limitations of their model and nuances in computer modeling of sytems.