Data Science and Analytics (MSc)
- 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
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:
- Domain knowledge
- Machine learning
- Operations research
- 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.
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
Telephone: 416-979-5000 ext. 3693