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.
Students enrolled in the Collaborative Program in Data Science must meet the requirements of their respective home units as well as those of the Collaborative Program. The requirements of the Collaborative Program do not, however, add to the number of credits students are required to accumulate by their home unit and the credit value of the degree remains the same. Consult the individual programs for detailed program requirements.
...with Collaborative Specialization in Data Science (5.0...5704 , PHYS 5002 , SYSC 5001 , SYSC 5003 , SYSC...
...with Collaborative Specialization in Data Science (5.0...higher excluding GEOG 5000, 5001 and 5905. Minimum...