M.Tech.| Computer Science & Engineering (CSE)

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Focuses on advanced concepts and research in computer science.
Covers areas such as machine learning, natural language processing, computer vision, and data mining.
Emphasises research, experimentation, and the development of computer solutions.
Includes a thesis or research project in collaboration with industry or academia.
Taught by experienced faculty with expertise in CSE.

Duration

2 Years

Programme Type

Part-time

Programme Fees

₹50,000/- per semester

Programme Regulations

2024–25

Programme Structure 2025

PDF is being worked upon by the Academic Council; the updated list will be shared once approved.

Eligibility Criteria

Candidates should have passed B.E./B.Tech. in CSE/ISE/IT/ECE/EEE (any circuit engineering departments) or M.Sc. in CS/IS/IT/Mathematics or MCA with a minimum of 50% marks (45% in the case of SC/ST candidates) from a recognised university.

Scope & Objectives

The goal of post graduate programs at CMRU is to develop professionals of high quality to cater to the needs of industry and academia. Such education will be based on a broad grasp of the fundamental principles of the sciences and scientific methods, a deep understanding of specific areas of specialisation, an ability to solve new problems, and a capacity to continually learn and interact with multidisciplinary groups.

Above all, CMRU aims at developing in its students a capacity for free and objective enquiry, courage and integrity, awareness and sensitivity to the needs and aspirations of society. The postgraduate programs are designed with the above goals in view. They include courses of study, seminars, project work, internships, and research leading to a thesis.

Programme Structure

Semester I

Mathematical Foundations for CSE
Advanced Database Management Systems
Advanced Machine Learning
Research Methodology & IPR
Pedagogy Studies

Semester II

Cloud Computing Tools
Deep Learning
Distributed Computing
Open Elective
Program Elective
Value Education
Mini Project

Semester III

Program Elective
Open Elective
Project Work – I
Internship

Semester IV

Project Work – II and Dissertation

Programme Assessment

Choice-Based Credit System (CBCS): The university follows CBCS, which allows students to choose courses and earn credits based on their performance

Grades and GPA: Students are awarded grades for each course in a semester, and their Semester Grade Point Average (SGPA) is calculated to measure their academic performance. Cumulative Grade Point Average (CGPA) is used to evaluate the overall performance of a student across all semesters.

Prescribed Curriculum: Each program has a prescribed curriculum or Scheme of Teaching and Evaluation, which includes the required courses, laboratories, and other degree requirements. It also incorporates SWAYAM and Massive Open Online Courses (MOOCs) offered by reputed institutions.

Auditing Courses: Students have the option to audit courses, which allows them to gain additional exposure without the pressure of obtaining a grade. This can give them an advantage in placements.

Evaluation System: The evaluation of students is comprehensive and continuous throughout the semester. It consists of Continuous Internal Evaluation (CIE) and Semester End Examination (SEE). CIE and SEE carry equal weightage of 50% each, resulting in a total evaluation of 100 marks for each course, regardless of its credit value.

Assessment Methods: Before each semester, faculty members may choose assessment methods such as assignments, seminars, quizzes, group discussions, case studies, practical activities, class presentations, industry reports, etc., with suitable weightage for each.

Semester End Examination: A Semester End Examination is conducted for all registered courses at the end of each semester. However, some courses that already have Continuous Internal Evaluation may not require a SEE.

Programme Outcome

PO1: Engineering Knowledge
Apply the knowledge of mathematics, science, engineering fundamentals, and computer science, along with a specialisation, to solve complex engineering problems.

PO2: Problem Analysis
Identify, formulate, review research literature, and analyse complex engineering problems using mathematics, basic sciences, and specialisation in computer science.

PO3: Design/Development of Solutions
Design solutions for complex problems using appropriate computer science knowledge for application in sectors such as healthcare, education, banking, and supply chain.

PO4: Conduct Investigations of Complex Problems
Use research-based knowledge and methods including the design of experiments, analysis and interpretation of data, and synthesis of information using cryptographic algorithms to provide valid conclusions.

PO5: Modern Tool Usage
Create, select, and apply appropriate techniques, resources, and IT tools (such as Wireshark, Metasploit, Cuckoo Sandbox, Yara Rules, Base64, VolUtility, Process Hacker, Hexinator) to build models using computer science.

PO6: The Engineer and Society
Apply contextual knowledge to assess societal, health, safety, security, legal, and cultural issues and responsibilities relevant to professional engineering practice.

PO7: Environment and Sustainability
Understand the impact of computer science and engineering solutions on societal and environmental contexts, and demonstrate knowledge of the need for sustainable development.

PO8: Ethics
Apply ethical principles and commit to professional ethics, responsibilities, and norms of engineering practice.

PO9: Individual and Team Work
Function effectively as an individual, and as a member or leader in diverse teams and multidisciplinary settings.

PO10: Communication
Communicate effectively on complex engineering activities with the engineering community and society, including writing reports, design documentation, presentations, and giving and receiving clear instructions.

PO11: Project Management and Finance
Demonstrate knowledge and understanding of computer science-related concerns and apply them to team roles, project management, and multidisciplinary environments.

PO12: Life–long Learning
Recognise the need for, and demonstrate the ability to engage in, independent and lifelong learning in the advancement of computer science.

Course Outcomes Visit

What Expertise Do You Gain?

Advanced knowledge of computer science and artificial intelligence.
Expertise in machine learning algorithms and techniques.
Understanding of natural language processing and computer vision.
Proficiency in data mining and big data analytics
Research and innovation skills in CSE

Career Opportunities

01
Software Developer
02
Hardware Engineer
03
Web Developer
04
Computer Programmer
05
Computational Automation
06
Computational R & D

Placements at CMR University

Tredence, Bengaluru, Inda – Rs.12,00,000 (CTC per annum)
EcoLab, Bengaluru, India – Rs. 9,00,000 (CTC per annum)
TESCO, Bengaluru, India – Rs. 8,00,000/-(CTC per annum)
EMPOWER, Bengaluru, India – Rs. 7,00,000/-(CTC per annum)
Ey Global Delivery Services, Bengaluru, India
Eurofins, Bengaluru, India – Rs.10,00,000/- (CTC per annum)
Esyasoft Technologies, Bengaluru, India – Rs.8,00,000/- (CTC per annum)
Maximus, Bengaluru, India – Rs. 7,50,000/- (CTC per annum)
CGI, Bengaluru, Indai – Rs. 6,00,000/- (CTC per annum)

How to apply?

Step 1 – Application Enquiry
On-call guidance with step-by-step expert instruction on how to complete the application form.

Step 2 – Selection Process
Candidates are shortlisted after document verification, interview, and the CMRUAT entrance exam.

Step 3 – Offer Letter
Provision of Offer Letter to commence further process.

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FAQs

CMRU offers one of the best M.Tech courses for CSE in Bangalore, and this program is a part-time, three-year postgraduate program. This degree offers students an opportunity to learn the advanced concepts of Computer Science and the various tools the industry uses to tackle critical problems that might arise during their careers. This program can also open many career opportunities because of the advanced practical knowledge one gains after this course.

CMRU is one of the best colleges for M.Tech in Computer Science in Bangalore. This course offers the best ways to apply theoretical and practical knowledge in relevant fields. This course also provides students with the opportunity to use and learn advanced software like Cuckoo, WireShark, Sandbox and many more. The many internships the students work at ensure that students have the confidence to tackle real industry problems.

M.Tech CSE in Bangalore is one course provided by CMRU that prepares students to tackle complex problems that one might face in the coding industry. This course ensures that the students are completely aware of all the nuances of Computer Science. Apart from theoretical and practical knowledge, students can also benefit from the ability to understand and apply the many tools and software like Metasploit, YaraRules and Process Hacker.

Students who have graduated with a minimum of 50% marks ( 45% in case of SC / ST) with a background in BE or B.Tech in the following stream –
CSE,
ISE,
IT,
ESE,
EEE or
M.Sc in CS, IS, IT or Mathematics or MCA.
Apart from the qualifications mentioned above, students should also have a passion towards Computer Science and an eagerness to learn new skills.

B.Tech. in CSE is one of the best courses available for securing a stable professional future. Study B.Tech. in CSE at one of the top private universities for Computer Science in Bangalore, CMR University. The software and IT industries are emerging fields with many innovations. An undergraduate course in Computer Science will help you build a strong career foundation.

M.Tech in Computer Science is in itself a specialisation with a lot of concepts, tools and principles. Each specialisation within this postgraduate degree has many other subjects to learn and master for a better understanding of that specific industry and concepts.

Tech in Computer Science in Bangalore have the required skill sets to transition their careers to more complex and rewarding positions like

Software Developer,
Computer Hardware Engineer,
Full Stack Developer,
Computation Automation,
AI Architect,
Data Scientist,
Machine Learning Expert and much more.

After completing this program, students can also handle roles that require leadership roles, thanks to the knowledge and experience gained during the program.

Yes, it is possible to pursue a PhD after completing M.Tech in Computer Science. Upon completing M.Tech in CSE, students have adequate knowledge to tackle the complexities of the industry; this course can also awaken the research curiosity among students, which further encourages them to pursue a PhD in Computer Science and other concepts like Artificial Intelligence.

M.Tech.| Computer Science & Engineering (CSE)