Data Science and Analytics (MSc)

by Toronto Metropolitan University Claim Listing

This unique 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 go on to pursue careers in industry

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img Duration

1-2 Years

Course Details

This unique 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 go on to pursue careers in industry, government or research. 

  • The program is offered as a one year full-time or two year part-time MRP option and two year full-time Thesis option.
  • The MSc in Data Science and Analytics is delivered in both lecture-based and hands-on lab learning environments where students can develop and apply their skills to complex, real-world datasets and data science and analytics problems.

Funding

  • At Toronto Metropolitan University, 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.

Research

  • As an urban innovation university, Toronto Metropolitan University offers 60+ cutting-edge, career-oriented graduate programs, as well as 125+ research centres, institutes and labs, in a wide range of disciplines. Our close connections with industry, government and community partners provide opportunities to apply your knowledge to real-world challenges and make a difference.

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
  • Toronto Branch

    350 Victoria Street, Toronto

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