Linear Algebra for Computer Science and Machine Learning

(10 customer reviews)

Last day of registration: November 15th, 2022


This product is currently out of stock and unavailable.

SKU: Chennai Mathematical Institute and Institute of Mathematical Sciences | Dates: 19 - 20 November, 2022 Categories: ,


Mode of workshop: Online

This workshop will introduce the basic concepts of linear algebra and their applications in computer science and machine learning. Linear algebra is a core component of numerous algorithms, and a foundation of data science and machine learning. This workshop will introduce the notions of vector spaces, linear independence, linear transformations, basis changes, eigenvectors and eigenvalues etc. and show their applications. The objective is to ensure that the students develop an intuitive understanding of what these notions and how are applied.

Day 1 : Saturday : 19th November, 2022

Module name: Basics 

Concepts covered :

  • Vectors
  • Vector Spaces
  • Basis and Span
  • Linear Independence
  • Matrices
  • Addition
  • Scalar Multiplication
  • Dot Product
  • Matrix Multiplication
  • Transpose
  • Inverse
  • Trace
  • Determinant Gaussian Elimination.

Learning Outcomes: Understand basic definitions and operations on Vectors and Matrices

Module name:  Linear Maps

Concepts covered :

  • Linear Transforms: Rotations, Reflections, Scaling, Shearing, Projection.
  • Affine Maps: Translation

Learning Outcomes: Understand Linear Maps and their applications

Day 2: Sunday : 20th November, 2022

Module name: Advanced Linear Algebra

Concepts covered :

  • Basis Changes
  • Fourier Transforms
  • Convolutions
  • Eigen Values and Singular Values
  • Pseudo-Inverse.

Learning Outcomes: Understand some advanced LA methods and applications

Module name: Linear Algebra Operations for Machine Learning

Concepts covered :

  • Tensors and  neural networks,
  • Hadamard product
  • 2D-Convolution
  • Reshaping
  • Lengths and Norms
  • Padding, Strides and Pooling.

Learning Outcomes : Understand LA operations and related methods used in ML

Session dates: 19 & 20 November 2022

Time:   Saturday & Sunday 10am to 1pm & 2pm to 4pm

Last date of Registration:  November 15th, 2022

Profile of the Instructor(s)

Prof Saket Saurabh:

Saket Saurabh is a Professor of Computer Science at the Institute of Mathematical Sciences, HBNI, Chennai, India. He has won many prestigious awards including the Swarnajayanti Fellowship in 2017, Shanti Swaroop Bhatnagar Prize in 2021 and two ERC grants. He has advised numerous PhD students and postdocs and published over 250 research papers in the area of algorithms. He is also affiliated with the University of Bergen, Norway.

Prof Pranabendu Misra:

Pranabendu Misra is an Assistant Professor in Computer Science at the Chennai Mathematical Institute, India. His main research interest lies in algorithms. Previously, he was a postdoctoral fellow at the Max-Planck Institute for Informatics, Germany and University of Bergen Norway. He has received Startup Research Grant(SRG) from Science and Engineering Research Board (SERB), India.

Eligibility & Fees

Basic Requirement:

School level Mathematics, Basic Computer Programming

Fees  for the workshop:

Students : Rs 590 ( Rs 500+GST)

Faculty : Rs 1180 ( Rs 1000+GST)


After attending all the sessions and submitting the project, we will provide you with a workshop completion certificate from NPTEL.

10 reviews for Linear Algebra for Computer Science and Machine Learning

  1. Akhlaque Ahmed

    Nice topic is selected. really its need of the hour.

  2. Dr. Gian Devi

    very excited for Linear Algebra for Computer science and machine learning…….waiting

  3. Dr. Gian Devi


  4. N C Santosh Kumar

    Good initiative, and very much needed in Digital Image Processing

  5. Krishna Kumar

    Very good

  6. Ankur Biswas

    Looking forward to the workshop.

  7. Shilpa S

    Nice topic…… looking forward for the workshop

  8. Dr. Gopal Shah

    Very good, arrange more

  9. G. Haripriya

    Good initiative, and very much needed in digital image processing

  10. PAMAR BALU KALE (verified owner)


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