collageThis 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.
Admissions Information
- Completion of a four-year undergraduate (or equivalent degree) from an accredited institution in engineering, science, business, economics or a related discipline
- Minimum grade point average (GPA) or equivalent of 3.00/4.33 (B) in the last two years of study
- Statement of interest
- Resumé/CV
- Transcripts
- Two letters of recommendation
- English language proficiency requirement
More information on admission requirements. Due to the competitive nature of our programs, it is not possible to offer admission to everyone who applies that meets the minimum entrance requirements for the program.
Check Application Deadline
Students are encouraged to submit applications prior to the first consideration date to increase their chances of securing financial support for their graduate studies. Applications received after the first consideration date will be accepted and reviewed based on spaces remaining in the program.
Skills Developed
- Domain knowledge
- Machine learning
- Math
- Operations research
- Programming
- Statistics
Sample Courses
- 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
Resources
- 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.
Graduate Admissions
Graduate Studies Admissions Office
11th Floor, 1 Dundas Street West
Toronto, ON
Telephone: 416-979-5150
Email: grdadmit@ryerson.ca
For information specific to programs, please see the program contact information below.
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
Email: ayse.bener@ryerson.ca
Igor Rosic
Graduate Program Administrator
Telephone: 416-979-5000 ext. 554836
Email: datascigrad@ryerson.ca
The Master of Science in Data Science and Analytics (MDSA) is a new program that has been developed with the objective of training students to work with data sets of varying sizes, formats and complexity. These skills will be applicable to areas from management and finance to conservation science, health care, astronomy, linguistics and urban planning.
Master of Science in Data Science and Analytics (MDSA) is a new program that has been developed with the objective of training students to work with data sets of varying sizes, formats and complexity. These skills will be applicable to areas from management and finance to conservation science, health care, astronomy, linguistics and urban planning.
MDSA is a new program that has been developed with the objective of training students to work with data sets of varying sizes, formats and complexity. These skills will be applicable to areas from management and finance to conservation science, health care, astronomy, linguistics and urban planning.
Data Science is an interdisciplinary field that draws on ideas from computer science, statistics and social sciences such as sociology or psychology. Data Science involves using tools from one or more of these disciplines for analysis or prediction purposes. This can include anything from analysing financial markets using machine learning methods to predicting future behavior based on past experience using regression analysis techniques
The program requires successful completion of 15 one-term graduate-level courses (45 credits). The degree is normally completed in three academic terms plus one summer term (1.5 years). Students may apply for admission on a part-time basis.
Ryerson’s Masters of Data Science and Analytics is normally completed in three academic terms plus one summer term (1.5 years). Students may apply for admission on a part-time basis.
The program requires successful completion of 15 one-term graduate-level courses (45 credits). The degree is normally completed in three academic terms plus one summer term (1.5 years). Students may apply for admission on a part-time basis.
The degree is completed in 1.5 years
The MDSA curriculum consists of 10 required courses and 5 electives. Students must take all 10 courses in the first year of the program in order to make progress toward their degree.
The MDSA program consists of 10 required courses and 5 electives. Students must take all 10 courses in the first year of the program in order to make progress toward their degree. The degree is normally completed in three academic terms plus one summer term (1.5 years).
Students who successfully complete this program will be able to work with data sets of varying sizes, formats and complexity, providing them with skills applicable to areas such as management, finance, conservation science, health care and urban planning.
- Data science masters is a new program at Ryerson University.
- Students will be able to work with data sets of varying sizes, formats and complexity.
- Applicable to areas such as management, finance, conservation science, health care and urban planning.
Conclusion
The MDSA program at Ryerson University is designed to provide students with the skills necessary to work with data sets of varying sizes, formats and complexity—skills that will be applicable in areas from management and finance to conservation science, health care, astronomy, linguistics and urban planning. Students who successfully complete this program will be able to work with data sets of varying sizes, formats and complexity providing them with skills applicable in areas such as management, finance conservation science health care astronomy linguistics urban planning
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