Computer Science: Applied Computing MScAC; Concentration: Artificial Intelligence in Healthcare

MScAC Program (Artificial Intelligence in Healthcare Concentration)

Minimum Admission Requirements

  • Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.

  • An appropriate bachelor's degree from a recognized university in an area such as life sciences, biochemistry, medical sciences, computer science, biotechnology, biostatistics, engineering, or a related discipline.

  • A standing equivalent to at least B+ in the final year of undergraduate studies.

  • Applicants should have sufficient academic undergraduate background in programming (ability to program and basic software engineering skills), calculus, statistics, a first- or second-year undergraduate course in statistics, linear algebra, and an undergraduate course that introduces concepts of healthcare and/or molecular biology. If courses were not taken prior to application to the program, please note that equivalent experience will be considered.

  • Applicants must satisfy the admissions committee of their ability to be successful in graduate courses in artificial intelligence (AI) and an industrial internship in healthcare. Applicants may be asked to do a technical interview as part of the application process.

  • The program will consider admitting candidates without an undergraduate degree in computer science, statistics, or a life sciences field, but who show a demonstrated aptitude to be an excellent candidate for this concentration. Applicants should be able to demonstrate a potential to conduct and communicate applied research at the intersection of computer science and a healthcare domain area. Background academic preparation to be successful in graduate-level computer science and medical sciences courses typically, though not always, includes intermediate or advanced undergraduate courses in the following topics:

    • Programming, software engineering, algorithms.

    • Statistical theory and/or mathematical statistics and linear algebra.

  • Students who are otherwise qualified but lack the appropriate background may be granted conditional admission, pending successful completion of additional background material as judged by the admissions committee.

  • Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS) with the following minimum scores:

    • Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.

    • IELTS: an overall score of 7.0, with at least 6.5 for each component.

  • If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.

  • Three letters of reference from faculty and/or employers, with preference for at least one such letter from a faculty member in computer science, biology, or data science.

  • Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.

  • Applicants must indicate a preference for the concentration in AI in Healthcare in their application. Admission to the AI in Healthcare concentration is competitive. Students who are admitted to the MScAC program are not automatically admitted to the AI in Healthcare concentration upon request.

Completion Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists

      • CSC2702H Technical Entrepreneurship.

    • 0.5 FCE in approved data science courses.

    • 0.5 FCE in approved AI courses.

    • 0.5 FCE in approved group 3 courses (visualization/systems/software engineering courses).

    • 0.5 FCE in approved Laboratory Medicine and Pathobiology (LMP) or Master of Health Informatics (MHI) courses.

  • A maximum of 1.0 FCE may be taken from outside the Department of Computer Science.

  • Students who lack the academic background in AI and/or statistics may be required to take additional courses in these areas.

  • An eight-month industrial internship, CSC2703H. The internship is coordinated by the department and evaluated on a pass/fail basis.

Mode of Delivery: In person
Program Length: 4 sessions full-time (typical registration sequence: FWS-F)
Time Limit: 3 years full-time

 

Computer Science