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CISC 372 Advanced Data Analytics
Inductive modelling of data, especially counting models; ensemble approaches to modelling; maximum likelihood and density-based approaches to clustering, visualization. Applications to non-numeric datasets such as natural language, social networks, Internet search, recommender systems. Introduction to deep learning. Ethics of data analytics.
LEARNING HOURS 120 (36L;84P)
Computing, Mathematics and Analytics – Specialization (Computing) – Bachelor of Computing (Honours)
...Data Analysis: CISC 271 Linear Data Analysis ; CISC 371 Nonlinear Data Analysis ; CISC 372 Advanced...
Computing, Mathematics and Analytics – Specialization (Computing) – Bachelor of Computing (Honours)
...Data Analysis: CISC 271 Linear Data Analysis ; CISC 371 Nonlinear Data Analysis ; CISC 372 Advanced...
Academic Programs
https://www.queensu.ca/academic-calendar/arts-science/academic-programs/
...Found ; BMED 372 Course BMED 372 Not Found...BLCK CANC; CHEM; CHIN; CISC; CLST; COCA; COGS...
Concurrent Education Degree Requirements
https://www.queensu.ca/academic-calendar/education/concurrent-education-degree-requirements/
...0, 272/3.0, 372/3.0 BIOL...0, 432/3.0 CISC 102 /3.0...