A degree in Engineering, Mathematics, or Computer Science is recommended, but not required.A passing grade on the prior learning assessment, conducted by the University of Toronto, for equivalent skills.The webinars will be recorded so if you are unable to attend you can watch the webinar recording at a time that is convenient to you. Data analytics is a broad term that includes everything from simply analyzing data to theorizing ways of collecting data and creating the frameworks needed to store it. Weekly webinars review key concepts and provide an opportunity for live interaction and Q&A with the instructors. Data analytics is a multidisciplinary field that employs a wide range of analysis techniques, including math, statistics, and computer science, to draw insights from data sets. Cover data analysis from both a classical and causal viewpoint.Use multiple linear and logistic regressions as predictive models.Formulate statistical tests to answer business questions.Design experiments to collect data that answer business or scientific questions.Professionals from every level or industry who work with analytics or data.Digital marketing and communication specialists.Finance, securities, and insurance professionals.Business associates, operations managers, project managers, and intelligence analysts.
This course is developed in partnership with the School of Continuing Studies at the University of Toronto. Concepts are solidified through individual and group based practical assignments. You'll get a math notation refresher, learn to form hypotheses, design experiments that collect valid data, test your hypotheses using statistical techniques, and work with causal models. In this course, you'll explore probability and descriptive statistics, cover data analysis from both a classical and contemporary viewpoint and learn to extract insight from datasets. Online learning with live recorded sessionsīuild on the skills you learned in Foundations of Data Science and get the grounding in basic statistics you need to successfully complete your Data Science certificate.
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