M.Tech Computer Science and Engineering (Data Science And Analytics)

Programme Overview

The M.Tech in Computer Science and Engineering (Data Science and Analytics) at MIT-WPU is a PG programme designed to equip Computer Science Engineers with advanced Machine Learning, Artificial Intelligence, and Data Science skills. The curriculum involves mastering computational systems' design, development, and analysis, emphasising high-performance, distributed, cloud, parallel, and scalable software and hardware.

Students of this programme delve into key technologies such as Cloud Computing, High-Performance Computing, Big Data Analytics, Image Analysis, and Data Visualisation. Through a comprehensive study of Big Data Analysis, Image Analysis, and advanced topics in Machine Learning and Artificial Intelligence, graduates are not just prepared for future jobs in the IT industry, but also equipped to apply their knowledge to real-world scenarios.

This programme at MIT-WPU inculcates the technologies and skills required for addressing real-world challenges in data-driven decision-making, making graduates highly sought after in fields ranging from finance to healthcare and beyond.

Duration
2 Years

Last Date To Apply : 15 July 2024
Programme Name

M.Tech Computer Science and Engineering (Data Science And Analytics)

Fee Per Year

Rs. 1,95,000




Highest CTC
INR 24 LPA

>
Eligibility

Indian Students

Minimum 50% aggregate score in graduation (4 years) of relevant Engineering Branch from UGC approved University or equivalent (at least 45% marks, in case of Backward class category candidate belonging to Maharashtra State only)
And
GATE Qualified (Obtained a positive score in GATE 2024, 2023, 2022) /MIT-WPU CET 2024 /PERA CET 2024
Or
Sponsored Candidate (Need 2 years of work experience after graduation, in field related to graduation)
Programme Highlights
  • Choice-based credit system pattern allows students flexibility in their academic pursuits whereas the curriculum includes MOOCs and interdisciplinary courses to enhance students' core competencies.
  • Emphasis on project-based learning ensures the practical application of theoretical knowledge.
  • A strong global alumni network offers valuable connections and support.
  • Scholarships for meritorious students support their academic journey.
  • State-of-the-art facilities equipped with the latest tools and technologies facilitate research and practical training.
  • Guest lectures, seminars, and workshops by industry experts, along with institutional collaborations with multinational corporations like Tata Technologies, Mercedes Benz, and Blue Star offer practical exposure.
  • Rural, national, and international immersion programmes help gain real-world experience and solve complex societal problems.
  • The MIT-WPU dedicated Centre for Industry-Academia partnerships (CIAP) supports students in securing internships with leading organisations such as Tata Motors, JCB, Volkswagen, and others, further enhancing their practical skills and industry knowledge, as well as placement opportunities in the same or other leading companies.
  • The programme allows students to specialize in Data Management for Machine Learning, Ethics for Data Science, Optimisation Techniques for Analytics, Natural Language Processing, etc.
Programme Outcomes
  • Adeptly apply advanced theoretical and practical knowledge to design, test, and adapt new computing technologies, fostering professional excellence for successful careers in industries and academia.
  • Critically analyse and offer techno-commercially feasible and socially acceptable solutions to computational problems, achieving professional excellence and effectively contributing to research and development (R&D).
  • Collaborate effectively on the development of innovative systems and optimised solutions in multidisciplinary domains, demonstrating high levels of professional and ethical values within global organisations and society.
  • Cultivate design thinking capabilities for innovation and entrepreneurship development, enhancing the capacity to innovate and lead in the field of Data Science and Analytics.
  • Conduct independent research, solve complex engineering problems, and function effectively as a team member or leader in software projects, contributing to real-world multifaceted problem-solving.
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