Data Science York University

Overview

The Data Science programme at York University provides a multidisciplinary education that bridges the gap between computer science and statistics. Students master the analytical techniques and computational methods required to generate meaningful insights from large-scale data sets.

Why Data Science at York University?

This programme distinguishes itself through specialised application streams that allow students to tailor their education to specific industries. You can choose to focus your studies on Business, Health, or Computational Arts, taking courses from renowned schools such as the Schulich School of Business.

A major highlight is the full-year capstone course taken in the final year of study. This experiential learning opportunity involves collaborating with public and private sector professionals to solve real-world data challenges. This hands-on research provides a significant competitive advantage in the job market.

The curriculum was developed in consultation with prospective employers to ensure graduates possess the exact skills needed for career success. Students have access to Keele Campus facilities and can participate in co-op or internship opportunities to gain further practical experience during their degree.

Tuition Fee Breakdown

• International fee: CAD 38465 per year
• National fee: CAD 8016 per year

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

Modules may include:

• Data Science
• Python Programming
• Applied Calculus
• Discrete Math for Computer Science
• Applied Linear Algebra
• Statistics
• Data Visualization
• Data Structures
• Machine Learning
• Data Analytics
• Ethics
• Communications

Careers with Data Science

Graduates are prepared for a variety of technical and analytical roles across diverse sectors. The programme's focus on both theoretical and applied perspectives ensures readiness for the modern workforce. Potential career paths include:

• Data scientist
• Data analyst
• Machine learning engineer
• Data architect
• Business analyst
• Market analyst
• Data engineer