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  • Faculty

    Faculty of Engineering and Technology

  • Department

    Department of Computer Science and Engineering

  • Campus

    Technology Campus (Peenya Campus)

  • Engagement Mode

    Full Time

  • Study

    B.Tech or B.E Students Minimum 2 Years ,Maximum 4 Years.

Overview

As per an NQR report, the estimated value of the worldwide Artificial Intelligence (AI) market stood at approximately US$ 119.78 billion in 2022. Forecasts indicate a substantial surge, projected to reach around US$ 1,591.03 billion by 2030. This growth trajectory reflects a recorded Compound Annual Growth Rate (CAGR) of 38.1% from 2022 to 2030.

The pursuit of an MTech in Artificial Intelligence and Machine Learning is an exciting journey into the realm of cutting-edge technology. This specialised programme delves deep into the intricacies of AI, focusing on its multifaceted applications across various industries. It offers a comprehensive understanding of machine learning techniques, enabling individuals to create intelligent systems capable of learning from data.

The MTech Artificial Intelligence and Machine Learning programme amalgamates theoretical knowledge with practical expertise, preparing graduates to tackle the complexities of today's AI-driven world and contribute significantly to innovation and technological advancement. Pursuing an MTech in Artificial Intelligence equips students with advanced skills in data analysis, neural networks, and algorithm development.

Program Objectives

  • A renowned establishment with a 62-year history
  • Accredited with NAAC A+ and ranked by NIRF
  • Faculty consisting of experts from prestigious institutions like IITs, IIMs, and more
  • Outstanding placement records, including the highest domestic package reaching Rs 45 LPA
  • Partnerships established with leading global universities such as MIT, University of Illinois, among others
  • State-of-the-art facilities including Advanced Learning Centre, Techno Center, NABL accredited Labs, Incubation Centre, etc.

Curriculum Details

Sl. No. Code Course Title Theory (h/W/S) Tutorials (h/W/S) Practical (h/W/S) Total Credits Max. Marks
1 19MIC501A Mathematics for Machine Learning 3 2 4 100
2 19DCS501A Programming for Data Science 3 2 4 100
3 19DSC502A Data Mining 3 2 4 100
4 19MIC502A Artificial Intelligence 3 2 4 100
5 19MIE501A Professional Elective-1 3 2 4 100
6 19FET509A Research Methodology & IPR 2 - - 2 50
7 19FET510A Audit Course 1 - - 0 0
Total 18 4 6 22 550
Total no. of Hours per Week 38

Sl. No. Code Course Title Theory (h/W/S) Tutorials (h/W/S) Practical (h/W/S) Total Credits Max. Marks
1 19MIC504A Artificial Neural Networks 3 2 2 5 100
2 19MIC505A Pattern Recognition 3 2 2 5 100
3 19MIE502A Professional Elective - 2 3 2 4 100
4 19MIE503A Professional Elective - 3 3 2 4 100
5 19MIE504A Professional Elective 4 3 2 4 100
6 19FET520A Audit Course 1 0
Total 16 8 6 22 500
Total no. of Hours per week

Sl. No. Code Course Title Theory (h/W/S) Tutorials (h/W/S) Practical (h/W/S) Total Credits Max. Marks
1 19MIC521A Internship 10 4 100
2 19MIC522A Group Project 15 8 200
Total - - 25 12 300
Total number of Contact hours per week 25 hours

Sl. No. Code Course Title Theory (h/W/S) Tutorials (h/W/S) Practical (h/W/S) Total Credits Max. Marks
1 19MIC523A Dissertation and Publication - - 24 24 400
Total 24 24 400
Total number of Contact hours per week 24 hours
Note:

Students are required to select Professional Elective course in the 1st Semester and 2nd Semester, from Elective list given as follows:

Stream / Specialization S.No Course Code Course Title
AI for Healthcare 1 19MIE501A Computational Intelligence
2 19MIE502A Deep Learning
3 19MIE503A Probabilistic Graphical Models
4 19MIE504A AI for Healthcare
5 20MIE507A Advanced Machine Learning
AI for Robots 1 19MIE505A Computer Vision
2 19MIE506A AI for Robots
3 20MIE508A Reinforcement Learning
4 19MIE501A Computational Intelligence
5 19MIE502A Deep Learning

Eligibility Criteria

  • BE / B. Tech. or equivalent in Electronics and Communication Engineering, Computer Science and Engineering, Electrical and Electronics Engineering, Automobile / Automotive Engineering, Mechanical Engineering, Aerospace / Aeronautics Engineering, Civil Engineering,Bio-Medical, Mechatronics, Information Science. Power Electronics and Drives BE / B. Tech.. or equivalent in Electrical
  • Admission Selection process for the University quota will be based on RUAS AT scores, while GATE/CUET-PG scores are also accepted and RUAS AT will be exempted for these candidates.

Structure

Total Fees Per Year
Rs. 213,000

Intake

Artificial Intelligence and Machine Learning 18 students.

Career Path

  • Machine Learning Engineer
  • AI Engineer
  • AI Data Annotation Expert
  • AI Solutions Architect
  • AI Consultant
  • Data Scientist
  • Computer Vision Engineer

FAQs

It is a full-time postgraduate programme focused on Artificial Intelligence and Machine Learning to develop intelligent systems and solutions using advanced computational methods.

Subjects span four semesters, including core AI and ML concepts, electives and project work. Detailed course structures are available per semester, emphasising technical and applied AI domains.

BE/B. Tech or equivalent in disciplines like CSE, ECE, EEE, Mechatronics, Mechanical, Civil, Aerospace, etc., are eligible. Admission is via RUAS AT or GATE/CUET-PG scores.

The total fee is ₹213,000 per year.

Apply online through RUAS Admissions Portal. You may take RUAS AT unless you have GATE or CUET-PG scores.

Graduates can work as AI Engineers, Machine Learning Engineers, Data Scientists, AI Consultants, or Computer Vision Engineers across sectors due to high industry demand.

Contact

Start your journey with MSRUAS

Dr. Rinki Sharma
Department of Computer Science and Engineering.

Admission 2025

ADDRESS

Vidya Soudha (Heritage Block)

M. S. Ramaiah University of Applied Sciences,

Gnanagangothri Campus

New BEL Road

MSR Nagar, Bangalore - 560054