Course Name: Multivariable calculus

Course abstract

This course is a basic course offered to UG and PG students of Engineering/Science background. It contains matrices computations involving rank, eigen values, eigen vectors, singularity transformations, (diagonalisation, Joradan canonical etc). It also convers vectors spaces, basis and dimension, linear transformation and their properties. Besides discussing the matrix theory, it also includes its applications in solving diverse science and engineering problems.


Course Instructor

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Prof. S. K. Gupta

Dr. S. K. Gupta is an Associate Professor in the Department of Mathematics, IIT Roorkee. His area of expertise includes nonlinear, non-convex and Fuzzy optimization. He has guided three PhD thesis and have published more than 40 papers in various international journals of repute.


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Prof. Sanjeev Kumar

Prof. Sanjeev Kumar is working as an associate professor with Department of Mathematics, IIT Roorkee. Earlier, he worked as a postdoctoral fellow with Department of Mathematics and Computer Science, University of Udine, Italy and assistant professor with IIT Roorkee. He is actively involved in teaching and research in the area of computational algorithms, inverse problems and image processing. He has published more than 55 papers in various international journals conferences of repute. He has completed a couple of sponsored research projects and written several chapters in reputed books published with Springer and CRC press. So far, he has completed three MOOC courses namely, Numerical Methods, Multivariable Calculus and Matrix Analysis with Applications under NPTEL program.
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Teaching Assistant(s)

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 Course Duration : Jan-Mar 2022

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 Enrollment : 14-Nov-2021 to 31-Jan-2022

 Exam registration : 13-Dec-2021 to 18-Feb-2022

 Exam Date : 27-Mar-2022

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Enrollment Statistics

Total Enrollment: 1235

Assignment Statistics




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Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.