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Bachelor of Science (B.Sc.) - Data Science

Overview

The B. Sc. in Data Science is an exciting programme that aims to build a broad foundation in mathematics, statistics, and computer science among students, through which they can learn a wide variety of analytics applications in Science, Engineering, Technology, and the Arts (SETA). The programme is application-focussed so that as students learn about mathematical, statistical, and computational tools and techniques, they continuously get to apply their learnings in a wide variety of domains.

The programme aims to attract hard-working and aspiring students who have the curiosity to learn new mathematical, statistical, and computational techniques, the ability to envisage and develop analytics solutions, the ability to extract insights from the analytic models, and the ability to communicate and collaborate with domain experts to improve/optimize systems. The subjects that students take include traditional branches of mathematics and statistics such as algebra, analysis, differential equations, descriptive statistics, inferential statistics, and R and Python programming, but also several cutting-edge offerings such as visual analytics, descriptive analytics, predictive analytics, prescriptive analytics, machine learning, deep learning, and artificial intelligence.

The programme aims to mold the students to become data science leaders of the future, to be able to creatively apply mathematical, statistical, and computational approaches to solve complex and challenging problems in Science, Engineering, Technology, and the Arts.

Course Duration

Three Years (Six Semesters)

Commence of the course


Course Duration


Mode of Study

Eligibility


Pre-University/Higher Secondary/10+2 Examinations or equivalent from any recognized Board or Council in any discipline.

Obtained at least 50% marks in the subjects taken in standard 12 or equivalent.


Special Features

  • Have an inside track to Global Leaders’ Alliance Fellowship
  • Take classes with Oxbridge/Ivy League faculty
  • Broad foundation in mathematics, statistics, and computer science
  • Learning a wide variety of analytics applications in Science, Engineering, Technology, and the Arts (SETA)
  • Internships in industry and academia, with live analytics projects
  • Contributing to and organising seminars and conferences

Course Structure

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