Data Science and Analytics (MSc)
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.
- 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:
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
- This program is part of the DMZ at Ryerson, where students 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
E-mail: grdadmit@ryerson.ca
www.ryerson.ca/gradstudies/future-students
Program Contacts
Dr. Ayse Bener
Graduate Program Director
Telephone: 416-979-5000 ext. 3155
E-Mail: ayse.bener@ryerson.ca
Igor Rosic
Program Administrator
Telephone: 416-979-5000 ext. 3693
Fax: 416-979-5153
E-Mail: datascigrad@ryerson.ca
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.
Funding
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.
Finding a Supervisor
Students should apply to the program first. Applications that meet the minimum requirements of the program will be forwarded to faculty members in the program for review. Successful applicants will be invited to visit the program and meet with faculty members that are interested in supervising them as a graduate student in their research group. A matching system is used to find the best students/supervisor match (using input from both applicants and faculty members). After a suitable match is determined, an official offer of admission will be sent with the supervisor named in the offer.