[Posted on 31/08/2026]: MTTS Trust has decided that no certificate will be issued for participation in this course. However, if the Trust takes any decision regarding certificates in the future, we will post it on the programme webpage.
[Posted on 31/08/2026]: Some important instructions are given below (below the Prerequisites section) for the selected candidates. Please check and follow them.
[Posted on 29/08/2028] Important Information for All Applicants
Linear Algebra: A Gateway to AI–ML
| Over 1,400 Applications Received |
Dear Applicant,
The MTTS Trust sincerely thanks you for your overwhelming interest in the online course “Linear Algebra: A Gateway to AI–ML”. Your response has been truly encouraging and reflects the faith and confidence that students, teachers and the wider mathematics community have placed in the MTTS Trust and its endeavours.
The Trust would genuinely like to accommodate every applicant who has expressed an interest in participating in this course. However, because of the interactive nature of the programme, limited availability of seats and practical constraints, we are able to accommodate only a limited number of participants in the interactive course.
In constituting the participant group, we have also tried to remain faithful to a fundamental philosophy of MTTS: to make meaningful mathematical learning accessible to students and teachers from different parts of India, including those from remote and less-served regions where opportunities for advanced mathematical learning may be limited.
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Selection of Participants Applicants who have been selected for the interactive course have been sent a separate email informing them of their selection. If you have not received a selection email, please do not regard this as a reflection on your academic ability or your interest in mathematics. With 1,431 applications and a limited number of seats, it was simply not possible for us to accommodate everyone. |
We are particularly grateful for the enthusiasm shown by applicants from different parts of the country. The geographical diversity of the applicant pool has reinforced our belief that programmes of this nature are needed on a much larger scale.
The Course Will Be Available Through Live Streaming
There is, however, good news for all applicants. The MTTS Trust has decided to live-stream all the sessions of the course so that the lectures can reach a much larger community beyond the limited number of interactive participants.
The live-streaming link will be shared on the MTTS webpage. Applicants will also receive an email with the relevant information and link. Thus, even if you have not been selected for the limited-seat interactive programme, you will still have an opportunity to attend and learn from all the lectures.
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An Open Forum for Questions and Discussion We also recognize that mathematics is best learnt through questions, discussion and interaction. Therefore, an open forum will be made available for the course. Those watching the live stream will also be able to post their questions and queries through the forum. We encourage all applicants to make full use of this facility and participate actively in the discussions. |
A Message of Thanks
The overwhelming response to this course is both humbling and encouraging for us. It demonstrates the strong and growing interest in mathematically grounded learning in areas such as Artificial Intelligence and Machine Learning. It also strengthens our resolve to explore ways of taking such programmes to a much larger number of students and teachers across the country.
The MTTS Trust remains committed to its long-standing philosophy of building mathematical skills, nurturing mathematical talent, and taking meaningful mathematical learning to students and teachers across India.
We once again thank each and every applicant for your interest, enthusiasm and, above all, your faith in the MTTS Trust. Whether you are participating directly in the course or joining us through the live stream, we look forward to having you as part of the MTTS learning community.
With warm regards,
MTTS Trust
Selection List
Click here to download the full list as a PDF fileSee the searchable list at this link.
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.
How to Apply
- Log In or Register: Visit the MTTS Application Portal. Log in to your existing account, or register for a new one if you are a first-time user.
- Locate the Programme: Navigate to the Academic Programmes menu. Find and click on Linear Algebra: A Gateway to AI & Machine Learning.
- Fill Out the Form: Complete the application by entering all required details.
- Save and Verify: Click Save and Verify, then follow the prompt to complete the verification. (Note: Unverified applications will not be processed.)
- Record Your Application Number: Write down your application number immediately. You will need to quote this number in all future communications regarding the programme.
⚠️ Important Submission Guidelines
- No manual submission needed: Once verified, you do not need to submit the form. It will be automatically submitted after the application deadline passes.
- Editing your application: You may log back in to edit your application at any time before the deadline. However, every edit requires you to re-verify.
- Draft status warning: If you edit your application but forget to re-verify it, it will revert to a “Draft.” We will not consider draft applications during the selection process.
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.
Instructions for Selected Candidates
The sessions of “Linear Algebra: A Gateway to AI & Machine Learning” (Programme Code: 26OCLA01) will be conducted through the Zoom platform.
To attend the sessions, please complete the following steps:
- Create a Zoom account using the same email ID that you used to apply for 26OCLA01. (Visit https://zoom.us/signup#/signup to create a zoom account, if you do not have one with your MTTS registered username as login id)
- Register for the Zoom sessions using the same email ID. The registration link will be available in your inbox on the 5dspace login portal, and will also be emailed to you separately.
- This is a one-time registration and will allow you to attend all the sessions of the programme.
Please complete your registration by 4:00 p.m. on Wednesday, 9 September 2026. Failure to register by the deadline may result in the cancellation of your selection.
After registration, you will receive a confirmation email containing the information required to join the sessions, subject to the approval process. This information is personalized and must not be shared with anyone else.
Join us for this exciting opportunity to strengthen your mathematical foundations and discover how Linear Algebra powers today’s Artificial Intelligence and Machine Learning.
Speaker
Dr. Swanand Khare (IIT Kharagpur)
Programme Details
Duration : 12/09/2026 to 31/10/2026
Coordinator: Dr. Prashantkumar Patel,
Dept. of Mathematics, Sardar Patel University, Vallabh Vidyanagar, Gujarat, India
Email : mtts.linearalgebraaimt@gmail.com
Important dates
- Start Date of Application: August 04, 2026
- End Date for Application: August 22, 2026
- Publication of Selection List: August 31, 2026
- Course starts on : September 12, 2026
Selection List
Click here to download the full list as a PDF fileSee the searchable list at this link.