- Faculty
Faculty of Engineering and Technology
- Department
Department of Computer Science and Engineering
- Campus
Technology Campus (Peenya Campus)
- Engagement Mode
Full Time
- Study
4 Years
Overview
Mathematics and computing graduates are in high demand due to their analytical and problem-solving skills. Industries ranging from technology and finance to data science and artificial intelligence actively seek individuals with a solid foundation in both mathematical modelling and computational techniques. According to a report from My Future, mathematicians and statisticians jobs are projected to grow by 31% between 2021 and 2031, much faster than the average for all occupations.
The BTech Mathematics and Computing is a dynamic and interdisciplinary course that bridges the realms of mathematics, computer science, and statistical analysis. As the world becomes increasingly data-driven, the B Tech Mathematics and Computing syllabus provides a strategic advantage, opening doors to diverse and high-demand career paths in various industries. After completing the programme, graduates emerge as versatile professionals ready to tackle complex real-world challenges.
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
Programme Educational Outcomes (PEOs)
- Provide students with a strong foundation in mathematics and computing along with breadth and foundational requirement in computing, science, engineering and humanities to enable them to devise and deliver efficient and safe solutions to challenging problems in Computer Science and inter-disciplinary areas
- Impart analytic and cognitive skills required to develop innovative solutions for R&D, to build creative, dependable and safe products for Industry based on dynamic societal requirements motivated and nurtured by sound theoretical and practical knowledge of time tested and long lasting principles of computer science, current tools and technologies
- Develop managerial and entrepreneurial skills inculcating strong human values along with social, interpersonal and leadership skills required for professional success in evolving global professional environments
Programme Outcomes (POs)
- Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems
- Identify, formulate, review research literature, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences
- Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations
- Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions
- Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations
- Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice
- Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development
- Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice
- Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings
- Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions
- Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments
- Recognize the need for and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change
Programme Outcomes (Pos)
- Apply principles and best practices in design of efficient algorithms and correct programs; build reliable, secure and robust software, making use of knowledge of computer architecture, systems software, networking, Web technologies distributed computing
- Use knowledge gained in both breadth courses in science and engineering and depth courses in mathematics and computing, solving problems of relevance to society, industry and R&D in an innovative manner
- Engage in lifelong learning by applying knowledge of fields of computer science and refining it and evangelizing applications and technologies to all interested communities
Curriculum Details
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max Marks |
|---|---|---|---|---|---|---|---|
| 1 | MTB101A | Engineering Mathematics 1 | 3 | 1 | 0 | 4 | 100 |
| 2 | PYB102A | Engineering Physics and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 3 | CEF101A | Engineering Mechanics | 3 | 0 | 0 | 3 | 100 |
| 4 | ECF102A | Elements of Electronics Engineering and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 5 | MEF103A | Engineering Drawing | 2 | 0 | 2 | 3 | 100 |
| 6 | LAN101A | Constitution, Human Rights and Law | 2 | 0 | 0 | 2 | 50 |
| Total | 16 | 1 | 6 | 20 | 550 | ||
| Total number of contact hours per week | 23 | ||||||
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max Marks |
| 1 | MTB102A | Engineering Mathematics-1 | 3 | 1 | 0 | 4 | 100 |
| 2 | CYB104A | Engineering Chemistry and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 3 | MEF104A | Elements of Mechanical Engineering and Work shop Practice | 2 | 0 | 2 | 3 | 100 |
| 4 | EEF105A | Elements of Electrical Engineering and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 5 | CSF106A | Elements of Computer Science and Engineering and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 6 | TSN101A | Professional Communication | 0 | 0 | 2 | 2 | 50 |
| Total | 14 | 1 | 10 | 21 | 550 | ||
| Total number of contact hours per week | 25 | ||||||
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max. Marks |
|---|---|---|---|---|---|---|---|
| 1 | MTB102A | Engineering Mathematics-2 | 3 | 1 | 0 | 4 | 100 |
| 2 | PYB102A | Engineering Physics and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 3 | CEF101A | Engineering Mechanics | 3 | 0 | 0 | 3 | 100 |
| 4 | ECF102A | Elements of Electronics Engineering and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 5 | MEF103A | Engineering Drawing | 2 | 0 | 2 | 3 | 100 |
| 6 | LAN101A | Constitution, Human Rights and Law | 2 | 0 | 0 | 2 | 50 |
| Total | 16 | 1 | 6 | 20 | 550 | ||
| Total number of contact hours per week | 23 | ||||||
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max. Marks |
|---|---|---|---|---|---|---|---|
| 1 | MTB102A | Engineering Mathematics-2 | 3 | 1 | 0 | 4 | 100 |
| 2 | CYB104A | Engineering Chemistry and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 3 | MEF104A | Elements of Mechanical Engineering and Work shop Practice | 2 | 0 | 2 | 3 | 100 |
| 4 | EEF105A | Elements of Electrical Engineering and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 5 | CSF106A | Elements of Computer Science and Engineering and Laboratory | 3 | 0 | 2 | 4 | 100 |
| 6 | TSN101A | Professional Communication | 0 | 0 | 2 | 2 | 50 |
| Total | 14 | 1 | 10 | 21 | 550 | ||
| Total number of contact hours per week | 23 | ||||||
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max. Marks |
|---|---|---|---|---|---|---|---|
| 1 | MCC201A | Complex Analysis and Vector calculus | 3 | 1 | 0 | 4 | 100 |
| 2 | MCC202A | Probability and Statistics | 3 | 0 | 0 | 3 | 100 |
| 3 | CSC201A | Discrete Mathematics | 3 | 1 | 0 | 4 | 100 |
| 4 | CSD201A | Data Structures Foundation | 3 | 0 | 0 | 3 | 100 |
| 5 | CSD202A | Logic Design | 3 | 1 | 0 | 4 | 100 |
| 6 | BAU201A | Entrepreneurship and Innovation | 3 | 0 | 0 | 3 | 100 |
| 7 | CSD204A | Python and Data Structures Laboratory | 0 | 0 | 2 | 1 | 50 |
| Total | 18 | 3 | 2 | 22 | 650 | ||
| Total number of contact hours per week | 23 | ||||||
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max Marks |
|---|---|---|---|---|---|---|---|
| 1 | MCC203A | Inferential Statistics | 3 | 1 | 0 | 4 | 100 |
| 2 | MCC204A | Integral Transforms | 3 | 1 | 0 | 4 | 100 |
| 3 | MCC205A | Linear Algebra | 3 | 0 | 0 | 3 | 100 |
| 4 | CSD206A | Design and Analysis of Algorithms | 3 | 0 | 0 | 3 | 100 |
| 5 | CSL201A | Formal Languages and Automation Theory | 3 | 0 | 0 | 3 | 100 |
| 6 | CSD208A | Programming Paradigms | 3 | 1 | 0 | 4 | 100 |
| 7 | BTN101A | Environmental Studies | 2 | 0 | 0 | 2 | 50 |
| 8 | MCL2O2A | Mathematics and Computing Laboratory | 0 | 0 | 2 | 1 | 50 |
| 9 | CSD208A | Programming Paradigms Laboratory | 0 | 0 | 2 | 1 | 50 |
| Total | 20 | 3 | 4 | 25 | 700 | ||
| Total number of contact hours per week | 27 | ||||||
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max Marks |
|---|---|---|---|---|---|---|---|
| 1 | MCC301A | Optimization Techniques | 3 | 1 | 0 | 4 | 100 |
| 2 | MCC302A | Partial Differential Equations | 3 | 1 | 0 | 4 | 100 |
| 3 | MCC303A | Applications of Probability and Statistics in Finance | 3 | 0 | 0 | 3 | 100 |
| 4 | CSD301A | Computer Networks | 3 | 0 | 0 | 3 | 100 |
| 5 | CSD203A | Microprocessors and Architecture | 3 | 0 | 0 | 3 | 100 |
| 6 | AID201A | Principles of Artificial Intelligence | 3 | 0 | 0 | 3 | 100 |
| 7 | CSL304A | Artificial Intelligence Laboratory | 0 | 0 | 2 | 1 | 50 |
| 8 | CSL301A | Computer Networks Laboratory | 0 | 0 | 2 | 1 | 50 |
| 9 | CSD205A | Microprocessors Laboratory | 0 | 0 | 2 | 1 | 50 |
| Total | 18 | 2 | 6 | 23 | 750 | ||
| Total number of contact hours per week | 26 | ||||||
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max Marks |
|---|---|---|---|---|---|---|---|
| 1 | CSC305A | Graph Theory and Optimization | 3 | 0 | 0 | 3 | 100 |
| 2 | CSC306A | Information Security and Protection | 3 | 1 | 0 | 4 | 100 |
| 3 | MCC309A | Quantum Computing | 3 | 1 | 0 | 4 | 100 |
| 4 | AIC203A | Machine Learning-1 | 3 | 1 | 0 | 4 | 100 |
| 5 | MCC310A | Parallel Algorithms for Scientific Computing | 3 | 0 | 0 | 3 | 100 |
| 6 | xxxxxx | Professional Core Elective-1 or Online Course | 3 | 1 | 0 | 4 | 100 |
| 7 | CSS301A | Seminar | 0 | 0 | 2 | 1 | 50 |
| 8 | MCL201A | Numerical Analysis Laboratory | 0 | 0 | 2 | 1 | 50 |
| Total | 18 | 4 | 4 | 24 | 700 | ||
| Total number of contact hours per week | 26 | ||||||
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max Marks |
|---|---|---|---|---|---|---|---|
| 1 | xxxxxx | Professional Core Elective-2 or Online Course | 3 | 1 | 0 | 4 | 100 |
| 2 | xxxxxx | Professional Core Elective-3 or Online Course | 3 | 1 | 0 | 4 | 100 |
| 3 | xxxxxx | Open Elective-1 or Online Course or Innovation Course | 3 | 0 | 0 | 3 | 100 |
| 4 | CSP401A or CSI401A | Project Work-1 or Internship | 0 | 0 | 12 | 6 | 200 |
| Total | 9 | 2 | 12 | 17 | 500 | ||
| Total number of contact hours per week | 23 | ||||||
| Sl. No. | Code | Course Title | Theory (h/W/S) | Tutorials (h/W/S) | Practical (h/W/S) | Total Credits | Max Marks |
|---|---|---|---|---|---|---|---|
| 1 | CSP402A | Project Work-2 or Internship | 0 | 0 | 24 | 12 | 300 |
| Total | 0 | 0 | 24 | 12 | 300 | ||
| Total number of contact hours per week | 24 | ||||||
| Stream | PCE-1 | PCE-2 | PCE-3 |
|---|---|---|---|
| Coding and Cryptography | 20MCE401A | 20MCE402A | 20MCE403A |
| Information Theory and Coding | Computational Number Theory and Algebra | Number Theory and Elliptic Curve Cryptography | |
| Mathematical Models | 20MCE404A | 20MCE405A | 20MCE402A |
| Introduction to Real Analysis | Topology | Computational Number Theory and Algebra | |
| Artificial Intelligence and Data Sciences | 20CSE405A | 20AIE407A | 20AIE404A |
| Computer Vision | Pattern Recognition | Artificial Intelligence and Healthcare | |
| Software Development | 20CSE401A | 20CSE402A | 20CSE403A |
| Software Architecture | Principles and Practices of Software Testing | Service Oriented Architecture | |
| Applied Mathematics | 20CSE401A | 20MCC301A | 20MCE403A |
| Advanced Mathematics | Optimization Techniques | Advanced Numerical Methods | |
| Data Science and Analytics | 20CSE407A | 20CSE304A | 20CSE408A |
| Data Sciences Foundation | Data Mining | Data Analytics |
Note:
Students are required to select:
One Professional Core Elective Course in the 6th Semester from PCE-1 Group.
Two Professional Core Elective Course in the 7th Semester from PCE-2 and PCE-3 Groups.
Eligibility Criteria
- Pass in 2nd PUC / 12th Std / Equivalent Exam with English as one of the Languages and obtained a Minimum of 45% of Marks in aggregate in Physics
and Mathematics along with Chemistry / BioTechnology / Biology / Electronics / Computer. - Admission to University quota will be based on COMEDK/JEE/KCET scores.
Structure
Fee Structure
| Total Fee for 1st year |
|---|
| 350,000 |
Intake
M&C - 30 students.
Career Path
- Data Analyst
- Statistician
- Actuary
- IC Technologist
- Computational Engineer
- Economic Researcher
FAQs
Graduates can pursue careers in data analytics, actuarial science, computational engineering, or research. They are also well-prepared for roles in AI, finance and higher studies, such as master's or doctoral programmes in related fields, due to their strong analytical background.
No, Mathematics and Computing is a distinct interdisciplinary programme that combines advanced mathematics, statistical analysis and computing. While it overlaps with CSE in areas like programming and algorithms, it places a stronger emphasis on theoretical and mathematical foundations.
If you have strong analytical skills and enjoy problem-solving, Mathematics and Computing is a great choice. It opens up opportunities across data science, finance, AI and research, making it ideal for students seeking a versatile and intellectually rigorous career path.
The scope is excellent with high demand in data science, finance, AI, research and analytics. The field is rapidly growing, with projected job growth for mathematicians and statisticians reaching 31% from 2021 to 2031, far above the average for all occupations.
B.Tech in Mathematics and Computing is a multidisciplinary programme that merges mathematical modelling, computational theory and data analysis. It equips students with critical skills to solve complex problems across various industries in a data-driven world.
Yes, it is a highly valuable programme with wide applications. RUAS’s curriculum, expert faculty, top-tier placement record and global university collaborations make it a strong option for students aiming for future-ready careers in high-demand, data-centric roles.
Contact
Start your journey with MSRUAS
Department of Computer Science and Engineering.
Contact
Email: hod.cs.et@msruas.ac.in
ADDRESS
