Matlab Programming for Numerical Computation

By Prof. Niket Kaisare   |   IIT Madras
Learners enrolled: 6364

About the course

MATLAB is a popular language for numerical computation. This course introduces students to MATLAB programming, and demonstrate it’s use for scientific computations. The basis of computational techniques are expounded through various coding examples and problems, and practical ways to use MATLAB will be discussed. By the end of this course, students would:

  • Learn basics of MATLAB programming
  • Get introduced to numerical methods for engineering problems
  • Will be able to use MATLAB to solve computational problems

Software Used

We will use MATLAB in this course. Course lectures, practice problems and assignments will use MATLAB.

MATLAB Online is a fully-featured browser-based version of MATLAB. With support from MathWorks, access to MATLAB Online is provided free-of-cost to all the enrolled students for the duration of this course.

Intended Audience

This is an introductory course, targeted towards scientists and engineers interested in using MATLAB programming for numerical computations. Examples taken in this course will be of generic interest to a wide range of students.This is a hands-on (like a laboratory) elective course. Intended audience include undergraduates, people with BE / ME / MS / MSc degrees; The course may be useful for PhD students also.


The students for this course are expected to know basics of linear algebra and calculus, at 12th standard level. These are also covered in Introductory Math course for Engineers (typically done in first year).

This course is intended to be practical (laboratory) course. Some prior background in programming will be useful, though not required. Likewise, students who have either completed or are currently doing “Numerical Methods” / “Computational Techniques” will find it easier to follow this course. Theoretical aspects of methods covered in this lab can be found in NPTEL course on "Numerical Methods for Engineers" (https://nptel.ac.in/courses/127106019).

Course Status : Completed
Course Type : Elective
Duration : 12 weeks
Category :
  • Computer Science and Engineering
  • Chemical Engineering
  • Multidisciplinary
  • Computational Biology
  • Electrical, Electronics and Communications Engineering
Credit Points : 3
Level : Undergraduate/Postgraduate
Start Date : 23 Jan 2023
End Date : 14 Apr 2023
Enrollment Ends : 06 Feb 2023
Exam Registration Ends : 17 Mar 2023
Exam Date : 29 Apr 2023 IST

Note: This exam date is subjected to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Course Outline

The course will be covered in twelve modules. Various aspects of MATLAB programming for numerical computation will be covered in these modules, with each module dedicated to an equivalent numerical topic. There will be self-study problems and graded assignment problems given each week, which are to be solved using MATLAB. The course plan is:

  1. Introduction to MATLAB Programming: This module will introduce the students to MATLAB programming through a few examples. Students who have used MATLAB are still recommended to do this module, as it introduces MATLAB in context of how we use it in this course
  2. Building your Code with MATLAB: This module covers MATLAB Script and Function files, loops, execution control, best-practices for MATLAB functions and tips on how to debug a MATLAB code.
  3. Approximations and Errors: Taylor’s / Maclaurin series expansion of some functions will be used to introduce approximations and errors in computational methods
  4. Linear Equations: The focus of this module is to do a quick introduction of most popular numerical methods in linear algebra, and use of MATLAB to solve practical problems.
  5. Nonlinear Equations: After introduction to bisection rule, this module primarily covers Newton-Raphson method and MATLAB routines fzero and fsolve.
  6. Numerical Differentiation and Integration: Methods of numerical differentiation and integration, trade-off between truncation and round-off errors, error propagation and MATLAB functions for integration will be discussed.
  7. Ordinary Differential Equations (ODE): Explicit ODE solving techniques in single variable will be covered in this module.

  8. ODE-IVP in Multiple Variables: This module will cover ODE solving in multiple variables, stiff systems, and practical problems. The importance of ODEs in engineering is reflected by the fact that two modules are dedicated to ODEs.

  9. Regression and Interpolation: The focus will be practical ways of using linear and nonlinear regression and interpolation functions in MATLAB.

  10. ODE-BVP and DAE: ODE-Boundary Value Problems; Differential Algebraic Equations

  11. Partial Differential Equations (PDEs): Practical ways of solving Hyperbolic and Parabolic PDEs

  12. Bringing it all together: Optimization andSolving interesting computational problems by bringing together multiple concepts

Update: Based on feedback from previous students, Final Exam will be based on the material covered in the first nine weeks of the course. Assignments will continue to be given in the last three weeks. This allows learners to "digest" the material and perform well in the exam.

This course was first introduced as an eight-week course in 2016. With feedback from students, this course was expanded to twelve-week (three credits) course in 2023. Some new aspects have been introduced and additional video lectures have been added to better explain some important concepts.

Thanks to the support from MathWorks, enrolled students have access to MATLAB for the duration of the course.

Books and references

Fausett L.V. (2007) Applied Numerical Analysis Using MATLAB, 2nd Ed., Pearson Education
Reference Book:
Chapra S.C. and Canale R.P. (2006) Numerical Methods for Engineers, 5th Ed., McGraw Hill
Related NPTEL Video Courses:
Computational Techniques:
Numerical Methods and Programming:

Instructor bio

Prof. Niket Kaisare

IIT Madras

Prof. Niket Kaisare is a Professor of Chemical Engineering in IIT-Madras. He works in the area of modeling, design and control for energy applications. He has over ten years of research/teaching experience in academia, and three-year experience in Industrial R&D. He uses computational software, including MATLAB, FORTRAN, Aspen and FLUENT extensively in his research and teaching.
Faculty web-page: http://www.che.iitm.ac.in/~nkaisare/

Course certificate

The course is free to enrol and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.

The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).

Date and Time of Exams
29 April 2023 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.

Registration url: Announcements will be made when the registration form is open for registrations.

The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then. Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.


Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Madras .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team

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