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DANA 4830: Dimension Reduction & Classification I
Course Format | Lecture 4.0 h + Seminar 0.0 h + Lab 0.0 h |
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Credits | 3.0 |
A core requirement in data analytics is the classification of a large group of records (items or objects) into different subgroups based on statistical criteria. The classification can be made easier if the number of dimensions of the data used is reduced. Students learn a number of techniques in reducing the number of dimensions in a data set without losing its latent structure. They also learn how to perform statistical classification into pre-defined groups. Topics include principal component analysis, factor analysis, multiple correspondence analysis, multivariate discriminant analysis, as well as stepwise techniques in regressions. Prerequisites: A minimum "C" grade in DANA 4810 and 4820.
Registration in this course is restricted to students admitted to the Post-Degree Diploma in Data Analytics and Post-Degree Certificate in Data Analytics.
Course Attributes: | |
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2nd Year Arts | |
2nd Year Science | |
Humanities | |
Lab Science | |
Science | |
Social Science | |
University Transferable |
Other Attributes: | |
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Offered online: | No |
Preparatory course: | No |
Repeat limit | 2 |
Additional fees: | $34.3 |
First offered: | Fall 2019 |
Last offered: | Fall 2025 |
Registration restrictions: | RP |
Outline(s): | No outline found. |
Course | Destination | Credit | Start to End |
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No active transfer agreements. |
Course | Destination | Credit | Start to End |
---|---|---|---|
No inactive transfer agreements. |
Offerings of this course:
Semester | CRN | Section | Seats | Waitlist | Days | Time | Room | Type | Instructor |
---|---|---|---|---|---|---|---|---|---|
Fall 2025 | 30807 | 001 | 31 | N/A | -T-R--- | 1630-1820 | Lecture | . TBA | |
Summer 2025 | 20290 | 001 | 12 | -T-R--- | 1430-1620 | B030 | Lecture | Quynh Nguyen | |
Spring 2025 | 10131 | 001 | 11 | M-W---- | 1430-1620 | A322 | Lecture | Quynh Nguyen | |
M------ | 1830-2125 | A314 | Exam | Quynh Nguyen | |||||
Fall 2024 | 30470 | 001 | 4 | -T-R--- | 1630-1820 | B152 | Lecture | Jonathan Agyeman | |
----F-- | 1830-2125 | B152 | Exam | Jonathan Agyeman | |||||
Summer 2024 | 20708 | 001 | 6 | -T-R--- | 1430-1620 | B008 | Lecture | Quynh Nguyen | |
----F-- | 1830-2125 | B008 | Exam | Quynh Nguyen | |||||
Spring 2024 | 10995 | 001 | 6 | -T-R--- | 1830-2020 | B027 | Lecture | Jonathan Agyeman | |
--W---- | 1830-2125 | B029 | Exam | Jonathan Agyeman | |||||
Fall 2023 | 30358 | 001 | 10 | -T-R--- | 1430-1620 | A272 | Lecture | Jonathan Agyeman | |
---R--- | 1830-2125 | A272 | Exam | Jonathan Agyeman | |||||
Summer 2023 | 20580 | 001 | 18 | M-W---- | 1630-1820 | B153 | Lecture | Quynh Nguyen | |
M------ | 1830-2125 | B153 | Exam | Quynh Nguyen | |||||
Spring 2023 | 10846 | 001 | 9 | M-W---- | 1830-2020 | B010 | Lecture | Jonathan Agyeman | |
----F-- | 1830-2125 | B018 | Exam | Jonathan Agyeman | |||||
Fall 2022 | 30670 | 001 | 8 | -T-R--- | 1630-1820 | A276 | Lecture | Jonathan Agyeman | |
----F-- | 1830-2125 | B018 | Exam | Jonathan Agyeman | |||||
Summer 2022 | 20468 | 001 | 6 | -T-R--- | 1630-1820 | B153 | Lecture | Quynh Nguyen | |
--W---- | 1830-2125 | B153 | Exam | Quynh Nguyen | |||||
Spring 2022 | 11060 | 001 | 6 | M-W---- | 1630-1820 | B252 | Lecture | Quynh Nguyen | |
-T----- | 1830-2125 | B155 | Exam | Quynh Nguyen | |||||
Fall 2021 | 30170 | 001 | 13 | -T-R--- | 1430-1620 | B023 | Lecture | Quynh Nguyen | |
M------ | 1830-2125 | B023 | Exam | Quynh Nguyen | |||||
Summer 2021 | 20572 | W01 | 8 | M-W---- | 1430-1620 | WWW | WWW | Quynh Nguyen | |
----F-- | 1830-2125 | WWW | Exam | Quynh Nguyen | |||||
Fall 2020 | 31539 | W01 | 4 | -T-R--- | 1630-1820 | WWW | WWW | Quynh Nguyen | |
M------ | 1830-2125 | WWW | Exam | Quynh Nguyen | |||||
Summer 2020 | 21160 | W01 | 3 | -T-R--- | 1630-1820 | WWW | WWW | Quynh Nguyen | |
-T----- | 1830-2125 | WWW | Exam | Quynh Nguyen | |||||
Fall 2019 | 31165 | 001 | 1 | -T-R--- | 1630-1820 | B022 | Lecture | Nathaniel Payne | |
M------ | 1830-2125 | B022 | Exam | Nathaniel Payne |