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Tuesday, May 18, 2021

IIIT-Delhi introduces Machine Learning and Cyber-Physical Systems specialisations in MTech degree

Admissions for the MTech (ECE) are now open and the last date for the submission of the online application is May 3, 2021. For details, visit 

By: Education Desk | New Delhi |
April 20, 2021 2:20:01 pm
iiit delhi, delhi collegs, 5g technology, wireless communication, lifi, light friedelite, internet connection india, research, emerging courses, college admissionIIIT-Delhi campus (Source: Official website)

The Indraprastha Institute of Information Technology (IIIT) Delhi today introduced two new specialisations – Machine Learning and Cyber-Physical Systems – for the students seeking admission in the MTech Electronics and Communication Engineering (ECE) programme. Admissions for the MTech (ECE) are now open and the last date for the submission of the online application is May 3, 2021. For details, visit 

The decision has been taken due to the evolving industry scenario that is witnessing the emergence of paradigm-shifting technologies like Artificial Intelligence (AI), Machine Learning (ML), and Internet of Things (IoT) among others.

According to a report published by Forbes magazine, the global Machine Learning market is projected to grow from $7.3 billion in 2020 to $30.6 billion in 2024, at a robust CAGR of 43 per cent. Hence, there is an urgent need to provide specialisations within ECE in the MTech degree to produce market-ready professionals.

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The newly launched MTech (ECE) Cyber-Physical Systems (CPS) programme aims to train and equip the students with industry-ready skillset on wireless networks and control systems. The programme presents a mix of rigorous theory, programming, and hands-on experiments on networked systems. Upon completion of the programme, the student will be able to join the industrial workforce and contribute to the wireless industry.

The MTech (ECE) Machine Learning (ML) programme is based on foundational and cutting-edge methods in these areas and is taught by faculty conducting pioneering research in the field. Students can opt for hands-on experience with real-world datasets through a thesis/capstone project as well. This programme is intended for students from ECE (and allied branches) who are looking to get a jump-start on a career in machine learning, with a strong focus on foundational math and theory, programming, and exposure to real-world applications.

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