MATH 2740

Mathematics for Data Science

(Lab required) This course introduces some of the mathematical tools used in Data Science. Topics include linear algebra: least squares, singular value decomposition, principal components analysis, and graph theory: centrality, social network theory, clustering. This course can only be used as an elective in an Honours, Major, or Joint Honours program in Mathematics. Prerequisites: [(a "B" or better in MATH 1210 or MATH 1211) or (a "C" or better in one of MATH 1220, MATH 1300, or MATH 1301)] and (a "C" or better in one of MATH 1232, MATH 1690, MATH 1700, MATH 1701, or MATH 1710).

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course_MATH_2740 cluster_equiv_1 cluster_equiv_2 MATH 2740 MATH 2740 MATH 1210 MATH 1210 B or better MATH 1210->MATH 2740 MATH 1232 MATH 1232 C or better MATH 1220 MATH 1220 C or better MATH 1220->MATH 1210 or MATH 1300 MATH 1300 C or better MATH 1300->MATH 1220 or MATH 1232->MATH 2740 MATH 1700 MATH 1700 C or better MATH 1700->MATH 1232 or MATH 1710 MATH 1710 C or better MATH 1710->MATH 1700 or

Fall 2019 sections

Lecture section

  • A01
    CRN: 18496
    Lecture Location: 136 Art Lab
    Dates: September 04 – December 06
    Time: 11:30–12:45, Tu.Th.

Lab sections

  • B01
    CRN: 18497
    Tutorial Location: 315 Machray Hall
    Dates: September 04 – December 06
    Time: 08:30–09:20, W.
  • B02
    CRN: 18498
    Tutorial Location: 315 Machray Hall
    Dates: September 04 – December 06
    Time: 09:30–10:20, W.
  • B03
    CRN: 18499
    Tutorial Location: 315 Machray Hall
    Dates: September 04 – December 06
    Time: 11:30–12:20, W.
  • B04
    CRN: 18500
    Tutorial Location: 124 Machray Hall
    Dates: September 04 – December 06
    Time: 14:30–15:20, W.