Data Science (Master of Science in Applied Computing)

by University of Toronto Claim Listing

The data science concentration offers students an advanced understanding of statistical and computer science methods, vigorous research training and the opportunity to test your knowledge in the real world through our applied research internship.

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img Duration

8 Months

Course Details

The data science concentration offers students an advanced understanding of statistical and computer science methods, vigorous research training and the opportunity to test your knowledge in the real world through our applied research internship. 

  • As a discipline, statistical science emerged from various scientific domains, established foundations and developed structure through mathematics, and has evolved to become inseparable from scientific computation, machine learning and computer science. Training in data science, as well as the field itself, captures all aspects of this evolution and makes it experiential for the trainee. The field of data science has emerged as a response to our increasing, and relentless, ability to generate data, particularly on a massive scale, and our reliance upon it in nearly every facet of human endeavour. The importance of the field has led to an entirely new type of professional – the Data Scientist. 
  • The Data Science concentration and the Artificial Intelligence concentration have both been recognized by Forbes as “The 10 Best Artificial Intelligence and Data Science Master’s Courses”. 

Why Data Science?
Diverse Skill Set: 

  • As a data scientist, you’ll blend mathematics, computer science, and business strategy. You’ll explore data, build statistical models, and communicate findings effectively.

Career Options: 

  • Data scientists work across various industries, from business and finance to healthcare and government. Your expertise can impact everything from emergency planning to national defense.

Program Requirements
Students must successfully complete six graduate level courses (totalling 3.0 Full Course Equivalents (FCEs)) as follows:

  • Two courses (1.0 FCE) chosen from the Department of Statistical Sciences course schedule. These must be STA-2000 level courses or higher. The course selection may also include a maximum of two courses (0.5 FCE) chosen from the STA-4500 level of six-week modular courses (0.25 FCE each)
  • Two courses (1.0 FCEs) chosen from the Department of Computer Science’s (CSC designator) course schedule in two different course groups. Course groupings can be found on the Computer Science website.
  • Two required courses (1.0 FCEs): Communication for Computer Scientists (CSC 2701H) and Technical Entrepreneurship (CSC 2702H).
  • An eight-month industrial internship, CSC 2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis. ‘Pass’ grades are awarded based on evaluations received from the industry/academic supervisors of the internship project and submission of an appropriately written final report, documenting the applied research internship.
  • Toronto Branch

    4th and 5th Floors 215 Huron Street, Toronto

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