Minor in Data Science

Minor in Data Science

In today’s data-driven society, Data Science provides a foundation for problem solving that impacts virtually all areas of the economy, including science, engineering, medicine, banking, finance, sports and the arts. Data science is an interdisciplinary field that focuses on analysing large amounts of data to identify inherent patterns, extract underlying models, and make relevant predictions.

The data science minor is designed to prepare students in wide disciplines who want to gain practical know-how of data analytics methods as it relates to their field of interest. It is designed to empower them to employ computational thinking and data science tools to solve practical business problems. The coursework consists of courses that cover the spectrum of Data Science to equip the students with knowledge of data analysis techniques and data-centric computation to address problems that require large data.

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Key Information

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Learning Outcomes

At the successful completion of this minor program, an Engineering Graduate will be able to

  • Learn and recognize the fundamental concepts of data science including data visualization, statistical analysis and machine learning.
  • Build skills and techniques of organizing and analysing big data for different applications.
  • Apply the data-driven modelling and machine learning algorithms to solve practical problems in engineering, social, scientific and business applications.

Eligibility Criteria

Student who has earned all credits of First Year of Engineering in Electronics Engineering / Mechanical Engineering/ Electronics and Computer Engineering.

Assessment Method

Evaluation will be done by a variety of tools including Open book tests, MCQs (multiple choice questions), Study of research papers, Internal Assessment tools and End Semester Examinations etc. Mini-Projects are offered to encourage project based learning among students.

List of Courses

  • Data Science principles and techniques
  • Introduction to Machine learning
  • Data Management and Information Systems
  • Fundamentals of Big Data analytics
  • Applied Project

Objectives

  • Apply principles of Data Science to the analysis of diverse problems.
  • Use software tools and algorithms from statistics, applied mathematics, Computer Science to model and analyze real-world data, communicate findings, and effectively present results using data visualization techniques.
  • Employ cutting edge tools and technologies to analyze large amounts Data.
  • Understand the ethical practices that are importantly and inevitably tied to data-driven decision-making.

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