Data Science Concordia University Montréal

Overview

The Data Science programme at Concordia University Montréal provides students with the essential analytical tools required to thrive in a modern, data-driven economy. This interdisciplinary course bridges the gap between theoretical mathematics and practical computational applications to solve complex real-world problems.

Students develop a robust foundation in statistical modelling and algorithmic thinking while gaining hands-on experience in dedicated data science laboratories. The curriculum is designed to evolve alongside technological advancements, ensuring graduates remain competitive in a rapidly changing professional landscape.

The teaching approach emphasises both technical proficiency and the development of vital soft skills.

Why Data Science at Concordia University Montréal?

This programme is distinguished by its integration of the Faculty of Arts and Science, offering a unique blend of mathematical rigour and versatile computer science training. Students benefit from exposure to cutting-edge facilities and a curriculum that highlights emerging fields like neural networks.

The institution provides significant experiential learning opportunities through its established Co-op programme. This allows high-achieving students to engage in paid work terms within government departments, insurance firms, and the banking sector, applying their classroom knowledge to professional environments.

Furthermore, the university offers specialised support and potential funding for eligible students, enhancing the accessibility of its high-quality undergraduate training. The Sir George Williams Campus provides a vibrant urban setting that fosters collaboration between aspiring data scientists and industry partners.

Tuition Fee Breakdown

• International fee: CAD 1075 per credit
• National fee: CAD 420 per credit

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

Syllabus

The curriculum integrates foundational training in mathematics with advanced computer science topics. Modules may include:

• Mathematics
• Statistics
• Data Science Labs
• Machine Learning
• Programming
• Databases
• Algorithms
• Artificial Intelligence
• Technical Writing
• Social and Ethical Dimensions of Technology

Careers with Data Science

Graduates are prepared to enter the workforce directly, occupying technical roles focused on data production, management, and sophisticated analysis. The programme equips individuals with the expertise needed to navigate various economic sectors that rely heavily on insightful data interpretation.

Common career paths include roles in quantitative and qualitative analysis, policy research, and econometric interpretation. Graduates often find employment in diverse fields such as telecommunications, finance, and provincial or federal government departments, where data-driven decision-making is paramount.

The combination of practical coding skills and statistical knowledge allows alumni to pursue positions in emerging areas like artificial intelligence and machine learning. This degree serves as a versatile platform for long-term professional growth in the global technology and business sectors.