A comprehensive and interdisciplinary introduction to data analytics using modern computing systems, with equal attention to fundamentals and practical aspects. Topics include sources of data, data formats and transformation, usage of spreadsheets and databases, statistical analysis, pattern recognition, data mining, big data, and methods for data presentation and visualization.

Essential skills and computational tools for working with data from a number of disciplines. Uses MATLAB for data analysis and visualization through basic statistics, numerical computing, and programming, with interdisciplinary applications ranging from image processing to financial computing, and more. Suitable for both Computer Science and non-Computer Science students.

0.5 course in Applied Mathematics, Calculus, Mathematics, Statistics (including Introductory Statistics) at the 1000-level or above.

Covers three basic concepts of data science together with the corresponding techniques: Sampling to estimate properties of a population (Bootstrap), random assignment and experiments to make causal inferences (randomization test), and model selection to enable good predictions (cross-validation). Emphasizes practical data handling and programming skills in Python.

1.0 courses from Mathematics, Calculus, or Applied Mathematics (numbered 1000 and higher) with a minimum mark of 60%.

(with a minimum grade of 60%) can be used to meet 0.5 of the 1.0 mathematics course requirements.

Three basic data science concepts and their corresponding techniques are explored while emphasizing practical data handling and programming skills in Python: Sampling to estimate the properties of a population (Bootstrap), random assignment and experiments to make causal inferences (randomization test), and model selection to enable good predictions (cross-validation).

the former Applied Mathematics 1412A/B, the former Applied Mathematics 1413.

Review of limits and derivatives of exponential, logarithmic and rational functions. Trigonometric functions and their inverses. The derivatives of the trig functions and their inverses. L'Hospital's rules. The definite integral. Fundamental theorem of Calculus. Simple substitution. Applications including areas of regions and volumes of solids of revolution.

An enriched version of Calculus 1000A/B. Basic set theory and an introduction to mathematical rigour. The precise definition of limit. Derivatives of exponential, logarithmic, rational trigonometric functions. L'Hospital's rule. The definite integral. Fundamental theorem of Calculus. Integration by substitution. Applications.

the former Physics 1029A/B, and the former Physics 1302A/B;

Explore foundational topics in astronomy, biology, chemistry, computer science, earth science, mathematics, and physics through an integrated questions-based approach. Small-group interactions and interdisciplinary laboratory experiments are designed to foster teamwork, interdisciplinary thinking, and the development problem-solving and critical-thinking skills.

Enrolment in Year 1 of the Western Integrated Science program and a minimum of 60% in each of

Enrolment in Year 2 of the Western Integrated Science program;

INTEGSCI 2002B

INTRODUCTION TO DATA SCIENCE

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