- 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 students Minimum 2 Years ,Maximum 4 Years.
Overview
According to a Precedence Research report, the global market size for data science platforms reached $112.12 billion in 2021. Projections suggest it will soar to approximately $501.03 billion by 2032, demonstrating a projected compound annual growth rate (CAGR) of 16.2% from 2023 to 2032.
Embarking on an MTech in Data Science and Engineering opens an immersive journey into a realm where technology intersects vast data landscapes. The MTech Data Science syllabus is meticulously crafted, covering a spectrum from foundational theories to advanced techniques such as Machine Learning, Big Data Analytics, and Data Engineering. Pursuing a Masters in Data Science in India offers a comprehensive education that delves into statistics, programming languages like Python and R, data visualization, and deep learning methodologies.
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 | Professional Elective-1 | 3 | 2 | 4 | 100 | |
| 5 | 19DSC503A | Data Processing | 3 | 2 | 4 | 100 | |
| 6 | 19FET508A | Research Methodology & IPR | 2 | - | - | 2 | 50 |
| 7 | 19FET509A | Professional Communication | 1 | - | - | 0 | 0 |
| Total | 18 | 4 | 6 | 22 | 550 | ||
| Total no. of Hours per Week | 24 | ||||||
| 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 | 19DCE504A | Advanced Data Processing | 3 | 2 | 2 | 5 | 100 |
| 3 | 19DSC502A | Professional Elective - 2 | 3 | 2 | 4 | 100 | |
| 4 | 19DSE503A | Professional Elective - 3 | 3 | 2 | 4 | 100 | |
| 5 | 19DSE504A | Professional Elective 4 | 3 | 2 | 4 | 100 | |
| 6 | 19FET520A | Value Education | 1 | 0 | |||
| Total | 16 | 10 | 4 | 22 | 500 | ||
| Total no. of 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 | 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 |
|---|---|---|---|
| Natural Language Processing | 1 | 19MIC502A | Artificial Intelligence |
| 2 | 19DSE502A | Distributed Computing | |
| 3 | 19DSE503A | Natural Language Processing | |
| 4 | 19DSE504A | Text Mining and Visualization | |
| 5 | 20DSE507A | Time Series Analysis | |
| Big Data Applications | 1 | 19MIC502A | Artificial Intelligence |
| 2 | 19DSE502A | Distributed Computing | |
| 3 | 19DSE506A | Big Data & Software Defined Networks | |
| 4 | 19DSE505A | Big Data & Healthcare |
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 Engineering, Mechatronics, Information Science, Telecommunication Engineering, Instrumentation Engineering, Medical Electronics
- 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
18 Seats
Career Path
- Statistician
- Business Intelligence Developer
- Data Scientist
- Data Architect
- Application Architect
- Database Administrator
- Data Consultant
FAQs
Candidates with a BE/B.Tech. in disciplines like Computer Science, ECE, EEE, Mechanical, Civil, Mechatronics, etc., are eligible. GATE, CUET-PG, or RUAS AT scores are considered for admission.
Yes, given its strong industry demand, top-notch faculty, NAAC A+ accreditation, international university tie-ups and placements up to ₹45 LPA, it offers high career value.
The course duration is a minimum of 2 years and can extend up to 4 years for completion.
It’s a full-time postgraduate programme focused on machine learning, big data, programming and deep learning to prepare professionals for the growing data-driven industry.
The curriculum includes four semesters with core subjects, electives and project work, covering topics in analytics, programming, data engineering and artificial intelligence.
Graduates can become Data Scientists, BI Developers, Statisticians, Data Architects, Application Architects, Database Administrators, or Data Consultants. .
Contact
Start your journey with MSRUAS
Ramaiah University of Applied Sciences
Heritage Building, Gnana Gangothri Campus New BEL Road, MSR Nagar, Bengaluru-58
Contact
Phone 080 4536 6616
Mobile +91 80100 04444
ADDRESS
