0057 - Data Science 4: Machine Learning
Course Description
Overview
This course will equip you with the basic machine learning and artificial intelligence (AI) tools for mining datasets, and extracting insights for decision making.
You will learn how to identify correlations and patterns in datasets, build more sophisticated predictive models using machine learning and deep learning software, and evaluate the performance of those models through individual and group based practical assignments.
This course is developed in partnership with the School of Continuing Studies at the University of Toronto
Who Should Enroll
- Business associates, operations managers, project managers, and intelligence analysts
- Finance, securities, and insurance professionals
- Digital marketing and communication specialists
- Professionals from every level or industry who work with analytics or data
What you will learn
- Find correlations between variables in a dataset.
- Identify clusters in data such as market segments.
- Predict future outcomes based on hidden relationships in historical data.
- Use tools to classify events or observations by type.
- Evaluate and combine models for best performance.
Course Details
Weekly webinars review key concepts and provide an opportunity for live interaction and Q&A with the instructors. 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.
Academic requirements
Required prerequisites:
- Foundations of Data Science and Statistics for Data Science OR
- A passing grade on the prior learning assessment, conducted by the University of Toronto, for equivalent skills
- A degree in Engineering, Mathematics, or Computer Science is recommended, but not required. Basic knowledge of programming and programming languages is strongly recommended.
System requirements
- Anaconda/Jupyter (software that you are required to install)
- Waterloo LEARN"