Program overview
Admission Requirements
Intakes

Last updated on 2025-05-30

Program overview

Program Overview

The Bachelor of Science in Data Sciences and Analytics program is a unique collaboration between the Faculty of Mathematics and Science and the Goodman School of Business. This program stands out as one of only two BSc programs in Canada that effectively combines financial analytics with computational data science. It aims to bridge the gap between computational data sciences and business analytics, producing graduates who possess a robust understanding of programming for big data, data infrastructures, and business intelligence.

 

Students will develop the ability to communicate complex data insights through advanced visualization techniques, supporting strategic decision-making in various business contexts. The program offers a comprehensive educational experience that prepares students for the evolving landscape of data science and analytics.

Program Structure

The Bachelor of Science in Data Sciences and Analytics program is designed to provide students with a well-rounded education in both computational data sciences and business analytics. The program is structured as follows:

  • Program Length: Typically spans over four years.
  • Students can choose between two concentrations: Financial Analytics or Computational Data Sciences.
  • Offers both Honours and Co-op options.
  • Focuses on experiential learning opportunities, including internships and co-op placements.
  • Encourages international opportunities for students to gain global perspectives.

 

Throughout the program, students will engage in various projects and practical experiences that enhance their learning and prepare them for real-world applications in the field of data science.

Featured Experiences

  • Co-op Opportunities: Students can participate in co-op placements to gain hands-on experience in the industry.
  • Experiential Learning: The program emphasizes practical learning through projects and case studies.
  • International Opportunities: Students have the chance to study abroad or participate in global projects.
  • Specialization Areas: Students can specialize in areas such as machine learning, artificial intelligence, and financial risk management.

Career Options

  • Data Scientist/Engineer: Responsible for analyzing and interpreting complex data to help organizations make informed decisions.
  • Big Data Solution Architect: Designs and implements big data solutions to manage and analyze large datasets.
  • Financial (Risk) Analyst: Evaluates financial data to assess risks and provide insights for investment decisions.
  • Data Analytics Consultant: Advises organizations on how to leverage data analytics for business improvement.
  • Predictive Analytics Modeller: Develops models to predict future trends based on historical data.

 

DISCLAIMER: The information above is subject to change. For the latest updates, please contact LOA Portal's advisors.

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