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Data Science (DATA) Courses

DATA 5000 [0.5 credit]
Data Science Seminar

Cloud based distributed systems, statistics, machine learning, use of complex ecosystems of tools and platforms, data ethics, and communication skills to explain advanced analytics. Students choose a project in Big Data management and/or analysis, deliver a paper and give a class presentation on their findings.

DATA 5001 [0.5 credit] (MAT 5818)
Fundamentals in Data Science and Analytics

Ethics in Data Science and Analytics, visualization and knowledge discovery in massive datasets; unsupervised learning: clustering algorithms; dimension reduction; supervised learning: pattern recognition, smoothing techniques, classification.
Precludes additional credit for STAT 5703.

DATA 5908 [1.0 credit]
Project - MSc


DATA 5909 [2.5 credits]
Thesis - MSc


DATA 5918 [1.0 credit]
Project - MIT


DATA 5919 [2.5 credits]
Thesis - MIT


DATA 5928 [1.0 credit]
Project - MEng


DATA 5929 [2.5 credits]
Thesis - MASc


DATA 5939 [2.5 credits]
Thesis - MCS


DATA 6909 [9.0 credits]
Thesis - PhD


Note: Not all courses listed are offered in a given year. For an up-to-date statement of course offerings for the current session and to determine the term of offering, consult the class schedule at central.carleton.ca.

Summer session: some of the courses listed in this Calendar are offered during the summer. Hours and scheduling for summer session courses will differ significantly from those reported in the fall/winter Calendar. To determine the scheduling and hours for summer session classes, consult the class schedule at central.carleton.ca