StudyCanada HomeUniversities in CanadaCarleton UniversityData Science, Analytics, and Artificial Intelligence
Specializations and variants
M.A.Sc. Data Science, Analytics, and Artificial Intelligence (5.0 credits)
M.C.S. Data Science, Analytics, and Artificial Intelligence (5.0 credits)
M.Eng. Data Science, Analytics, and Artificial Intelligence (4.5 credits)
M.I.T. Data Science, Analytics, and Artificial Intelligence (5.0 credits)
M.Sc. Data Science, Analytics, and Artificial Intelligence (5.0 credits)
Ph.D. Data Science, Analytics, and Artificial Intelligence (1.5 credits)
Program pathways and conditions
These tables reproduce the source requirements for the indicated period. Official interpretation is the responsibility of the university.
Pathway 1
| M.A.Sc. Data Science, Analytics, and Artificial Intelligence - thesis pathway (5.0 credits) | ||
| 1. 1.0 credit in: | 1.0 | |
| DATA 5000 [0.5] | Introduction to Data Science | |
| DATA 5001 [0.5] | Fundamentals in Data Science and Analytics | |
| 2. 0.5 credit in approved SYSC electives (see DSAAI program website for list of applicable electives) | 0.5 | |
| 3. 0.5 credit in approved electives not in SYSC (see DSAAI program website for list of applicable electives) | 0.5 | |
| 4. 0.5 credit in elective from any participating DSAAI unit | 0.5 | |
| Note: 0.5 credit from above electives must be in applications of artificial intelligence or machine learning (see DSAAI program website for list of applicable electives) | ||
| 5. 2.5 credits in: | 2.5 | |
| DATA 5929 [2.5] | Thesis - MASc | |
| Total Credits | 5.0 |
Pathway 2
| Requirements - thesis pathway (5.0 credits) | ||
| 1. 1.0 credit in: | 1.0 | |
| DATA 5000 [0.5] | Introduction to Data Science | |
| DATA 5001 [0.5] | Fundamentals in Data Science and Analytics | |
| 2. 0.5 credit in approved COMP electives (see DSAAI program website for list of applicable electives) | 0.5 | |
| 3. 0.5 credit in approved electives not in COMP (see DSAAI program website for list of applicable electives) | 0.5 | |
| 4. 0.5 credit in elective from any participating DSAAI unit | 0.5 | |
| 5. 0.5 credit from above electives must be in applications of artificial intelligence or machine learning (See DSAAI program website for list) | ||
| 6. 2.5 credits in: | 2.5 | |
| DATA 5939 [2.5] | Thesis - MCS | |
| Total Credits | 5.0 |
Pathway 3
| M.Eng. Data Science, Analytics, and Artificial Intelligence - coursework pathway (4.5 credits) | ||
| 1. 1.0 credit in: | 1.0 | |
| DATA 5000 [0.5] | Introduction to Data Science | |
| DATA 5001 [0.5] | Fundamentals in Data Science and Analytics | |
| 2. 1.0 credit in approved SYSC electives (see DSAAI program website for list of applicable electives) | 1.0 | |
| 3. 0.5 credit in any graduate-level SYSC course | 0.5 | |
| 4. 1.0 credit in approved electives from two units not in SYSC (see DSAAI program website for list of applicable electives) | 1.0 | |
| 5. 1.0 credit in electives from any participating DSAAI unit | 1.0 | |
| Note: 0.5 credit from above electives must be in application of artificial intelligence or machine learning (see DSAAI program website for list of applicable electives) | ||
| Total Credits | 4.5 |
Pathway 4
| M.I.T. Data Science, Analytics, and Artificial Intelligence - thesis pathway (5.0 credits) | ||
| 1. 1.0 credit in: | 1.0 | |
| DATA 5000 [0.5] | Introduction to Data Science | |
| DATA 5001 [0.5] | Fundamentals in Data Science and Analytics | |
| 2. 0.5 credit in approved ITEC electives (see DSAAI program website for list of applicable electives) | 0.5 | |
| 3. 0.5 credit in approved electives not in ITEC (see DSAAI program website for list of applicable electives) | 0.5 | |
| 4. 0.5 credit in elective from any participating DSAAI unit | 0.5 | |
| Note: 0.5 credit from above electives must be in applications of artificial intelligence or machine learning (see DSAAI program website for list of applicable electives) | ||
| 5. 2.5 credits in: | 2.5 | |
| DATA 5919 [2.5] | Thesis - MIT | |
| Total Credits | 5.0 |
Pathway 5
| M.Sc. Data Science, Analytics and Artificial Intelligence - thesis pathway (5.0 credits) | ||
| 1. 1.0 credit in: | 1.0 | |
| DATA 5000 [0.5] | Introduction to Data Science | |
| DATA 5001 [0.5] | Fundamentals in Data Science and Analytics | |
| 2. 0.5 credit in approved MATH or STAT elective (see DSAAI program website for list of applicable electives) | 0.5 | |
| 3. 0.5 credit in approved electives not in MATH or STAT (see DSAAI program website for list of applicable electives) | 0.5 | |
| 4. 0.5 credit in elective from any participating DSAAI unit | 0.5 | |
| Note: 0.5 credit from above electives must be in applications of artificial intelligence or machine learning (see DSAAI program website for list of applicable electives) | ||
| 5. 2.5 credits in: | 2.5 | |
| DATA 5909 [2.5] | Thesis - MSc | |
| Total Credits | 5.0 |
Pathway 6
| Requirements (1.5 credits): | ||
| 1. 0.5 credit in: | 0.5 | |
| DATA 5001 [0.5] | Fundamentals in Data Science and Analytics | |
| 2. 1.0 credit in elective, approved by supervisor (see DSAAI program website for list of applicable electives) | 1.0 | |
| 3. 0.0 credit in: | ||
| DATA 6907 [0.0] | Doctoral Comprehensive | |
| 4. 0.0 credit in: | ||
| DATA 6908 [0.0] | Doctoral Proposal | |
| 5. 0.0 credit in: | 0.0 | |
| DATA 6909 [0.0] | Thesis - PhD | |
| Total Credits | 1.5 |
Courses
These courses were identified on the program source page. Their presence does not mean they are all required in every pathway.
Sources and references
Reference year : 2026-27
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/grad/gradprograms/dsa/