Machine Learning Work Integrated Project I - CMPT 3830

In this course, students work in groups on machine learning projects based on real-world business cases and solutions. Students will learn the project lifecycle and acquire the multidisciplinary teamwork and strategy skills required for employment. While working in domain-specific cohorts on applied machine learning business cases using problems and datasets developed by local companies, students will also explore the business case for employing machine learning solutions. By working through applied machine learning projects, students will begin to develop a portfolio of work and learn the practical skills of conceptualizing and progressing through a basic project workflow as a team. This course is taught by local experts and industry guest lecturers, so students will have the opportunity to engage industry experts and network with potential employers. Examples of domain-specific cohorts may include health, fintech, social enterprise, and environmental science and natural resources. Students must complete this course in a term directly before CMPT 3835 (Machine Learning Work Integrated Project II). Note for international learners: This is not work-integrated learning, and there are no practicum hours assigned to this course. International learners do not require a co-op work study permit for this course.

Note: Prerequisite BUSD 1003, ENGL 2510 Co-requisite: CMPT 3510 Restricted to Machine Learning Analyst

This course will provide students with the opportunity to interact with local industry and expose students to domain-specific projects. Students will work in domain-specific cohorts on real-world applied machine learning problems supplied by local companies while exploring the business case for employing machine learning solutions. In working through the applied machine learning projects, students will also begin the development of a portfolio of work and learn the practical skills of conceptualizing and progressing through a basic project workflow as a team. Students will have the opportunity to engage with industry experts throughout the project and network with potential employers. Examples of domain-specific cohorts may include health, FinTech, social enterprise, and environmental science and natural resources. Students must take this course in a term directly before CMPT 3835 (Machine Learning Work Integrated Project II).

Note: Prerequisite BUSD 1003 Co-requisite: CMPT 3510 Restricted to Machine Learning Analyst


Term Duration Schedule Class Section Open Studies

Edmonton

Fall Aug 29 - Dec 16, 2022 Mon: 09:30 am - 12:30 pm
40681 A01 No
Term Duration Schedule Class Section Open Studies

Edmonton

Fall Aug 29 - Dec 16, 2022 Mon: 09:30 am - 12:30 pm
40683 H01 No

To take this course, you must be enrolled in one of the related programs:

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