Data Science minor

General information and requirements

A minor consisting of 18 credit hours is available in Data Science. This Data Science minor focuses on developing computational and analytical skills needed to turn large volumes of data into insight. Our ability to produce and collect enormous quantities of heterogeneous data is rapidly growing. The term Big Data has been coined to address the incredible value of intelligent analysis of large volumes of data to support crucial business, financial and strategic decisions. Individuals capable of turning vast quantities of data, in other words Big Data, into insight are required in today’s workplace. Individuals with this ability, often called data scientists, are highly sought after in a variety of industries, from healthcare to finance to business consultancy.

The Data Science minor will enable students enrolled in a diverse set of non-Computer Science STEM programs – applied mathematics, physics, etc. – to acquire the computational and data analytic skills needed to be competitive in tomorrow’s job market. The minor will focus on:

• Developing a basic understanding of computational tools for data analytics.
• Gaining working knowledge over a range of problems, methods and systems for performing data analysis for real – life data sets.
• Attaining a good understanding of the applications of data science in a variety of domains.
• Acquiring critical problem solving skills to extract knowledge and understanding from large volumes of data. 

If the current trends are any indicator, students with a Data Science minor will be highly sought after in a whole array of industries.

Course requirements

Students must complete the following courses:

• CSCI 1040U – Introduction to Programming for Scientists
• CSCI 2000U – Scientific Data Analysis
• CSCI 2010U – Data Structures

• One of:

• CSCI 3030U – Database Systems and Concepts or
• CSCI 3031U – Databases for Scientists

• Two of:

• CSCI 4030U – Big Data Analytics or
• CSCI 4050U – Machine Learning, Theory and Application or
• CSCI 4150U – Data Mining or
• CSCI 4210U – Information Visualization

Optional courses

Students who are interested in pursuing additional courses in this area are encouraged, but not required, to take the following courses:

• CSCI 3010U – Simulation and Modelling
• CSCI 4060U – Massively Parallel Programming
• CSCI 4220U – Computer Vision
• CSCI 4610U – Artificial Intelligence