Program Overview

The Master of Data Analytics (MDA) program is a one-year professional science master’s program beginning each September, consisting of two terms of on-campus courses (fall and winter) followed by a summer experiential learning opportunity, which in most cases will be paid experience working in industry.

The MDA program will provide you with the skills needed to be proficient in technical data analytics and apply those skills in a specific field, or as a generalist practitioner. Experiential learning in the summer term will ensure that you are ready to transition into a data analytics career in the public or private sector by providing valuable, practical experience applying those skills.

Our curriculum is flexible. If you have a significant background in a data analytics-related field, such as Statistics or Computer Science, you will have the opportunity to deepen your knowledge in that discipline while broadening your level of expertise in the other. If you do not have a degree in Computer Science or Statistics but have a strong quantitative and computational background, our curriculum will allow you to rapidly develop a fundamental skill set in technical data analytics related to these areas. For more details on admissions requirements see here.

Students enter the program at the start of the fall semester. The fall and winter curriculum is designed to ensure that you will:

  1. Develop strong, foundational, technical data analytic skills from statistics and computer science, learning state-of-the-art data analytics software and methods;
  2. Learn about a specific field where data analytics is used and see practical applications of data analytics to solve problems in that area;
  3. Be able to effectively communicate data analytics techniques and discoveries to both technical and non-technical audiences, and develop ethical judgement when conducting or assessing analyses;
  4. Have a competitive advantage when finding your summer position for the experiential learning component of the program.