- 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 or B. Tech or equivalent degree 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; or
Medical Electronics
Candidates who belong to SC/ST categories are given a different qualifying mark as per government notifications
Candidates should have the equivalent qualification approved by Association of Indian Universities.
Should have proof of proficiency in English with a minimum TOEFL score of 8
Structure
| Tuition Fees | University Fees | Total Fees |
|---|---|---|
| 175000 | 40000 | 215,000 |
Intake
Data Science and Engineering 18 students.
Career Path
- Statistician
- Business Intelligence Developer
- Data Scientist
- Data Architect
- Application Architect
- Database Administrator
- Data Consultant
FAQs
Yes. As per the UGC Reference Letter No: F 8 – 22/2013(CPP1/PU) dated 21 July, 2016, Ramaiah University of Applied Sciences is recognised by the University Grants Commission.
Yes. Ramaiah University of Applied Sciences is approved by the AICTE. Refer to Approval Reference Number F. No. South-West/2020 – 21/1 – 7161814455, dated 30 June 2020.
RUAS has 10 Faculties that together offer more than 90+ programmes in different fields of study and of different levels. For programme-specific details.
At RUAS, students can apply for a programme online or in person. For details on how to apply online
The fee structure for programmes differs based on the level of the programme and the student’s category.
As per the rules of the University, the entire fee amount must be collected at the beginning of the year and cannot be paid per semester.
The Gnanagangothri Campus and the Technology Campus have well-planned hostel facilities for students. However, the on-campus accommodation at Technology Campus is currently restricted to female students only.
Students from both campuses can also opt for private, off-campus accommodation.`
Once you have applied for a programme, you will be given login credentials like a User ID and a Password. Using these, you can then log in and choose the day and time of your test from the given options. For more details and instructions.
While the actual date varies every year, admissions for UG programmes close in the month of August, while those for PG programmes close in September.
The Faculties of Engineering & Technology, Art & Design, and Mathematical & Physical Sciences are housed in the Technology Campus. Therefore, all programmes offered by these Faculties are conducted in the Technology Campus.
Similarly, the Gnanagangothri Campus on New BEL Road is home to the Faculties of Dental Sciences, Pharmacy, Hospitality Management and Catering Technology, Management & Commerce, Life & Allied Health Sciences, School of Social Sciences and School of Law and the programmes offered by each of them
No. While MSRIT is an autonomous college under VTU, RUAS is a private university. Both institutions are, however, managed by the same group.
Yes. The University offers students scholarships. Students can also opt for scholarships offered by the state and central governments, or by private organisations and charities.
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