Academic Calendar - 2024
Western University Academic Calendar. - 2024
Data Science 2100A
MATHEMATICS FOR DATA SCIENCE
Mathematical background for students wanting to take Data Science 3000A/B, but missing background in linear algebra and calculus. Vector and matrix algebra, norms, linear dependence, inverses, vector spaces, eigenvectors and eigenvalues, Gradients, Hessians, basics of optimization. All concepts are explained in the context of data science examples.
Antirequisite(s): Mathematics 1600A/B, Applied Mathematics 1411A/B.
Prerequisite(s): 1.0 courses from Mathematics, Calculus, or Applied Mathematics (1000 and higher) with a minimal grade of 60%. Data Science 2000A/B or Integrated Science 2002B can be used to fulfil 0.5 of the requirements.
Extra Information: 3 lecture hours/week, 1 tutorial hour/week.
Course Weight: 0.50
Breadth:
CATEGORY C
i
Subject Code: DATASCI
This Course is Mentioned in the Following Calendar Pages:
Data Science 2100A
MATHEMATICS FOR DATA SCIENCE
Mathematical background for students wanting to take Data Science 3000A/B, but missing background in linear algebra and calculus. Vector and matrix algebra, norms, linear dependence, inverses, vector spaces, eigenvectors and eigenvalues, Gradients, Hessians, basics of optimization. All concepts are explained in the context of data science examples.
Antirequisite(s): Mathematics 1600A/B, Applied Mathematics 1411A/B.
Prerequisite(s): 1.0 courses from Mathematics, Calculus, or Applied Mathematics (1000 and higher) with a minimal grade of 60%. Data Science 2000A/B or Integrated Science 2002B can be used to fulfil 0.5 of the requirements.
Extra Information: 3 lecture hours/week, 1 tutorial hour/week.
Data Science 3000A/B - INTRODUCTION TO MACHINE LEARNING
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Faculty of Science | Statistical and Actuarial Sciences | CERTIFICATE IN DATA SCIENCE
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