Mathematics Training and Talent Search Programme

The Mathematics Training and Talent Search (MTTS) Trust is pleased to announce an eight-session online weekend course on “Linear Algebra: A Gateway to Artificial Intelligence (AI) and Machine Learning (ML)”, designed for students and teachers interested in understanding the mathematical foundations of modern Artificial Intelligence (AI) and Machine Learning (ML).

The course will commence on September 12, 2026, and will be conducted over weekends. Each session will consist of 75 minutes of MTTS-style highly interactive session followed by 45 minutes of hands-on programming using Python.

The course will be taught by Dr. Swanand Khare (IIT Kharagpur).

Why this course?

Linear Algebra is one of the foundational subjects on which modern machine learning heavily relies. High-dimensional data such as images, video and text embeddings are represented as matrices and vectors. Linear transformations play a crucial role in feature representation when weight matrices multiply the inputs in a hidden layer of a neural network. Linear regression models require solving an overdetermined system of linear equations in the least-squares sense. The eigenvalue–eigenvector decomposition of the covariance matrix, or the SVD of the data matrix, enables representing the data in a lower-dimensional space, making the subsequent computation efficient. Low-rank approximations pave the way for LoRA updates of deep networks in the presence of streaming data. We will cover these concepts along with several applications and hands-on exercises in the course on “Linear Algebra: A Gateway to AI–ML”. The main objective of this course is to familiarize participants with these important concepts and computational techniques in linear algebra and demonstrate their use in AI and ML applications. A first course in linear algebra is a pre-requisite for this course. Basic knowledge of Python will be an added advantage; however, we will conduct one session on matrix computations with Python at the beginning of the course.

Course Highlights

• Instructor: Dr. Swanand Khare (IIT Kharagpur)
• Mode: Online
• Commencement: September 12, 2026
• Schedule: Weekend classes
• Duration: 8 sessions
• Each Session: 75-minute interactive lecture + 45-minute hands-on Python session
• Registration: Compulsory; No Registration Fee
• Coordinator: Dr. Prashantkumar Patel,
  Dept. of Mathematics, Sardar Patel University, Vallabh Vidyanagar, Gujarat, India

Who can apply?

• Students pursuing undergraduate studies (6th Semester onwards) or higher studies in Mathematics and allied areas.
• Teachers teaching Mathematics and allied subjects at the Undergraduate or Postgraduate level.
• Seats are limited, and selection will be based on eligibility and the number of applications received.

Prerequisites

Participants are expected to have completed a first course in Linear Algebra. Familiarity with Python is desirable but not mandatory, as an introductory session on matrix computations using Python will be conducted at the beginning of the course.

Join us for this exciting opportunity to strengthen your mathematical foundations and discover how Linear Algebra powers today’s Artificial Intelligence and Machine Learning.

Programme Poster