B.Sc. (Hon.) Data Sciences and Analytics
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Overview
The B.Sc. Data Sciences program enables students to engage in the domains of data mining, analysis, and predictive modelling. The programme’s curriculum has more of application-oriented learning and the curriculum mainly stresses on the mastery of basic mathematics, statistics, and computer science. The emphasis of the programme is to expose students to advanced concepts, developments, and techniques in the realm of data analytics.
The B.Sc. Data Sciences program is developed by the members of the faculty based on interactions with various universities, financial institutions, and industries. The curriculum is outcome based and it imbibes required theoretical concepts and practical skills in the domain. By undergoing this programme, students develop application-oriented learning skills, critical, analytical thinking, and problem-solving abilities for a smooth transition from academic to real-life work environment.
Students are trained in communication skills and interdisciplinary topics to enhance their scope. In addition, the students also can enrol into one-year Ramaiah Advanced Post Graduate Diploma which will give them a leading edged and make the students more versatile, generating wide range of opportunities including registering for master’s and Ph.D. programme in a chosen subject area, if one wishes to be considering teaching in a university.
Objective
- The programme’s goal is to produce graduates with application-oriented learners, critical, analytical, and problem-solving skills, and ability to think independently, to pursue a career in data sciences
- To impart knowledge, understanding and cognitive abilities in data sciences, research, practice, and interdisciplinary courses
- To develop competencies and practical skills required for effective problem solving and right decision making in data sciences
- The programme exposes students to advanced concepts, developments, and techniques in the realm of data analytics
Highlights
FOUNDATIONAL COURSES (FC)
Six foundational courses are offered as part of the programme to provide interdisciplinary and multidisciplinary perspectives for the students
- The campus is in the neighbourhood of premier institutions like ISRO, IISc, RRI, CIPR, NIAS and so on, which provides students with ample opportunities to engage in academic and non-academic programs of these institutions
- Hostel accommodations for students at a reasonable price
- Enriched academic eco-system provides inter-disciplinary perspectives and opportunities to engage for students of social sciences
- Highly ranked for its innovation by QS IGUAGE, NIRF & KSURF
- The campus is in the neighbourhood of premier institutions like ISRO, IISc, RRI, CIPR, NIAS and so on, which provides students with ample opportunities to engage in academic and non-academic programs of these institutions
- Collaborations with foreign universities for exchange programs (University of Illinois System, USA, International Medical School)
- The campus is located in the heart of the city (it is a boon to students keen on attending seminars, conferences, and cultural events in Bengaluru)
- Our emphasis on applied brilliance translates into a campus that is buzzing with activity, whether in the form of guest lectures, seminars, workshops and industry events or student-organised activities and competitions.
- With 9 faculties from different areas of study, multidisciplinary thinking is a way of life at RUAS.
- From a host of eateries and cafes to convenience stores and coffee vending machines, our campus has been designed and developed to ensure that the needs of every student are met.
- With access to RUAS’s numerous facilities, students are encouraged to participate in co-curricular sports and cultural events.
- The University offers a range of on-campus accommodation options. Third-party, off-campus hostels are also available.
Structure
Study Domains
- FC
Foundation Courses
- CC
Core Courses
- GE
General Electives
- DSE
Discipline Specific Electives
- SEC
Skill Enhancement Courses
- AECC
Ability Enhancement Compulsory Courses
Course Progression
Course | Credits |
---|---|
Compulsory Foundation Course 1 (CFC 1) | 4 |
Compulsory Foundation Course 1 (CFC 2) | 4 |
Linear Algebra (CC) | 5 |
Programming in R Lab (CC) | 5 |
Data Visualization (CC) | 5 |
Ability Enhancement Course 1 | 2 |
Key
- Theory
- Tutorials
- Practicals
Course | Credits |
---|---|
Compulsory Foundation Course 3 (CFF 3) | 4 |
Compulsory Foundation Course 4 (CFF 4) | 4 |
Inferential Statistics (CC) | 5 |
Regression Techniques and Time Series Analysis (CC) | 5 |
Python Programming Lab (CC) | 5 |
Generic Elective 1 | 5 |
Skill Enhancement Course – 1 (SEC-1) | 2 |
Key
- Theory
- Tutorials
- Practicals
Course | Credits |
---|---|
Multivariate Analysis (CC) | 5 |
Database Management Systems (CC) | 5 |
Data Pre-processing (CC) | 5 |
Generic Elective 2 | 5 |
Ability Enhancement Course 1 | 2 |
Key
- Theory
- Tutorials
- Practicals
Course | Credits |
---|---|
Operations Research & Optimisation Techniques ion Techniques (CC) | 5 |
Data Warehousing & Mining (CC) | 5 |
Artificial Intelligence (CC) | 5 |
Generic Elective-3 | 5 |
Skill Enhancement Course – 2 (SEC-2) | 2 |
Key
- Theory
- Tutorials
- Practicals
Course | Credits |
---|---|
Machine Learning (CC) | 5 |
Big Data (CC) | 5 |
Deep Learning (DSE) (Track 1) | 5 |
Introduction to Computational Social Sciences (DSE) (Track 2) | 5 |
Open Elective-1 (SSS) | 5 |
Key
- Theory
- Tutorials
- Practicals
Course | Credits |
---|---|
Dissertation/Project (CC) | 6 |
Computing for Data Sciences (DSE) (Track 1) | 5 |
Risk Management (DSE) (Track 2) | 5 |
Open Elective-2 (SSS) | 5 |
Key
- Theory
- Tutorials
- Practicals
Course | Credits |
---|---|
Cloud Computing (DSE) (Tack 1) | 5 |
Advanced Computing for Data Sciences (DSE) (Tack 1) | 5 |
Advanced Machine Learning (DSE) (Tack 1) | 5 |
Applied Social Network Analysis with Python (DSE) (Tack 2) | 5 |
Applications in Economics (DSE) (Tack 2) | 5 |
Consumer Behavior (DSE) (Tack 2) | 5 |
Open Elective-3 (SSS) | 5 |
Key
- Theory
- Tutorials
- Practicals
Course | Credits |
---|---|
Capstone/project/ Internship | 6 |
Key
- Theory
- Tutorials
- Practicals
Details
FEES
- Rs. 175000 Per Annum
Members of the Board of Studies (External)
- Dr Manisha Chakrabarty, Professor, Indian Institute of Management, Calcutta
- Dr Praphul Chandra, Professor, International School of Engineering, Bengaluru
- Dr Biswabrata Pradhan, Professor, Indian Statistical Institute, Calcutta
- Dr Supriyo Ghose, Professor, IFMI Business School, Bengaluru
- Dr Govind R. Kadambi, Pro Vice-Chancellor (Research), RUAS, Bengaluru
Admissions
Indian Nationals
Fees & Scholarships
- Rs175000 Per Annum
Start your journey with RUAS
Downloads
- Programme Regulations pdf | 906.1 KB
- Programme Specifications pdf | 837.5 KB