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Interdisciplinary Studies, Data Science

Unit 1: A Mean Resume

 You are a Human Resources (HR) professional, looking to recruit a new staff member at your Data Analytics firm. For the job posting, you must determine the most appropriate job requirements, education qualifications, and salary information and therefore, you must analyze the current trends to build the profile. Students will learn about measures of central tendency, measures of spread, and data visualizations, and apply these concepts to recommend a salary for the job posting. (30 hours)

Unit 2: A Candidate of Best Fit

Continuing as the HR professional, you have received over 1000 resumes for the job and you don’t have the time to go through each one manually – what can you do to efficiently shortlist the candidates? Students will learn how to work with categorical data, as well as analyze the relationships between data. The concept of text mining is introduced and students will use programming to run keyword algorithms to shortlist the candidates. (22 hours)

Unit 3: Churn it Back Around

 The music program at your school is folding. Students are churning (dropping out) unexpectedly. Your job is to identify the characteristics that are causing this churn rate. In this unit, students will learn about machine learning (how to train computers), as well as databases, and data privacy and ethics. Combining these concepts, students will propose a new plan for the music program to ensure a better retention rate.  (22 hours)

Unit 4: Data Over Borders

The Minister of International Trade has hired you to provide insight on the state of imports and exports in Canada. You will need to review Canada’s trading partners over time and analyze specific trading partners. Students will learn about international trade, importing and exporting of goods, and then perform analysis of the data to recommend a plan to the Minister.  (26 hours)

Final Assessment

 The Capstone Project is worth 30% of the overall grade and consists of 2 parts: an executive summary and a presentation. It assesses the student’s ability to use the concepts taught in the course into a culminating data science analysis.  (10 hours)

Course content developed by our partner, Virtual High School.

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