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Data Science and Analytics (MSc)

Three graduate students working on a laptop in GRADSpace

Program Overview

Format: Full-time, Part-time

Degree Earned: Master of Science

This unique one-year Master of Science (MSc) degree program enables students to develop interdisciplinary skills and gain a deep understanding of technical and applied knowledge in data science and analytics. Graduates are highly trained, qualified data scientists who can pursue careers in industry, government or research.

PDF fileDownload the program brochure

Students working at computer stations in a classroom

At a Glance

  • Completion of a four-year bachelor’s degree in engineering, science, business, economics or related discipline
  • Minimum grade point average (GPA) or equivalent of 3.00/4.33 (B) in the last two years of study
  • Two letters of recommendation
  • Statement of interest
  • Resumé/CV

Prospective students are expected to demonstrate working knowledge of statistics, data structures and algorithms, databases and R programming. These prerequisites can be documented through prior completion of university or college level courses equivalent to the following courses that are offered at Ryerson University’s G. Raymond Chang School of Continuing Education:

  • CIND 123: Data Analytics: Basic Methods (formerly CKME 132: Statistics and R Programming)
  • CIND 110: Data Organization for Data Analysts (formerly CKCS 110: Database Management)
  • CCPS 305: Data Structures and Algorithms

For detailed fees information visit Fees by Program.

  • Domain knowledge
  • Machine learning
  • Math
  • Operations research
  • Programming
  • Statistics
  • Advanced Data Visualization
  • Bayesian Statistics and Machine Learning
  • Data Mining and Prescriptive Analysis
  • Designs of Algorithms and Programming for Massive Data
  • Interactive Learning in Decision Processes
  • Machine Learning
  • Management of Big Data and Big Data Tools
  • NLP (Text Mining)
  • Social Media Analytics
  • Students can apply to participate in DMZ programming, where they have the opportunity to create their own startups or work with companies engaged in big data and data science.
  • Students may have direct access to various international partners and/or exchange programs to enhance their learning experience.
  • Ryerson’s Big Data Initiative (BDI) spans many academic units and research areas. The Data Science Laboratory, RC4 High Performance Computing Facility, and Privacy and Big Data Institute are part of Ryerson’s cross-university BDI agenda to develop new tools and apply them to advance organizational performance across sectors.
  • The program engages with various industry and government partners from diverse domains.

Admissions Contact

Graduate Studies Admissions Office
11th Floor, 1 Dundas Street West
Toronto, ON
Telephone: 416-979-5150
Fax: 416-979-5153

Program Contacts

Dr. Ayse Bener
Graduate Program Director
PhD, Information Systems, London School of Economics
Research areas: machine learning, recommender systems and big data applications
Telephone: 416-979-5000 ext. 3155

Igor Rosic
Program Administrator
Telephone: 416-979-5000 ext. 3693
Fax: 416-979-5153

Marcia Hon , external link

Student Profile, external link

Marcia Hon (data science and analytics MSc alumna) reflects on how the program propelled her career to land a job with the Centre for Addiction and Mental Health.

How to Apply

Once you’ve made an informed choice about which program(s) you are going to apply to, preparing your application requires careful research and planning.


At Ryerson, we understand that pursuing graduate studies is a significant financial investment. Funding comes from a combination of employment contracts (as a teaching assistant), scholarships, awards and stipends. There are a number of additional funding sources – internal and external – available to graduate students that can increase these funding levels.