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CISC 372 Advanced Data Analytics
CISC 372 Advanced Data Analytics Units: 3.00
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)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 271 and [3.0 units in STAT or STAT_Options]).
Offering Faculty: Faculty of Arts and Science
Computing, Mathematics and Analytics – Specialization (Computing) – Bachelor of Computing (Honours)
...477 . ii. Data Analysis: CISC 271 ; CISC 371 ; CISC 372 ; CISC 473 ; STAT 361 ; STAT...
Computing, Mathematics and Analytics – Specialization (Computing) – Bachelor of Computing (Honours)
...477 . ii. Data Analysis: CISC 271 ; CISC 371 ; CISC 372 ; CISC 473 ; STAT 361 ; STAT...
Concurrent Education Degree Requirements
https://www.queensu.ca/academic-calendar/education/concurrent-education-program/degree-requirements/
...3.0, CISC 102 /3.0, CISC 203...272 /3.0, ARTH 372 /3.0, BIOL...