IDC4U Interdisciplinary Studies: Data Science – Grade 12 (University)

IDC4U Data Science online is one of over 160 secondary school courses that Blyth Academy Online offers.

Courses Offered

 
 
 
 
 
 
 
 

IBM LogoPREREQUISITE: Any university or university/college preparation course

GRADE: 12 (University)

AVAILABILITY: Blyth Academy Online

THE ONTARIO CURRICULUM: Interdisciplinary Studies

CREDIT CROSSOVER: Although Interdisciplinary Studies (IDC4U) courses focus on different subject matter, the IDC4U course code can only count as one credit on a student’s transcript, even if multiple IDC4U courses are taken. For example, a student that has completed IDC4U – Artificial Intelligence and IDC4U – The Elite Athlete will only earn one credit in total on their final transcript. Each IDC4U course (along with the final grade) will show, however, a credit value of zero will be applied to the second IDC4U course. This also applies to students using IDC4U as one of their top six marks when applying to university; one only IDC4U course may be used as an achieved credit out of the six.

IBM's Cognitive Class logoBlyth Academy Online is proud to be working with IBM’s Cognitive Class to offer a Grade 12 course in Data Science.

As the amount of information available to us becomes greater and greater, the ability to effectively make use of that data is fast becoming one of the most important skills of the 21st century.

Starting with asking the right questions, looking at how to obtain the relevant data, and then how to process it and present a conclusion, IDC4U Data Science online will give students the data literacy that will provide them with great opportunities in the fastest growing job market in Canada.

In IDC4U Data Science online, students will use data in case studies involving recruitment, social media and e-commerce. They will gain experience with the field’s most commonly used computer language, R, and work with IBM’s Data Scientist Workbench.

UNIT ONE

Theory & Foundation: Introduction to DSW, Intro to R, Basic Stats
Essential Question: How is Talent Acquisition shaped by Data Science?
  • In this unit, students will be given a human resources case study for a North American data analytics consulting company called Fireside Analytics Inc. The company has received thousands of resumes for a manager position it is seeking to fill. Students will be given the task to use publicly available data from Statistics Canada data to analyze the relationship between university degree studies and average salary.

UNIT TWO

Processes: Text Analytics & Word Clouds
Essential Question: What are ways that data mining data visualization can provide relevant information?
  • In this unit, students will be given a human resources case study for a North American data analytics consulting company called Fireside Analytics Inc. The company has received thousands of resumes for a manager position it is seeking to fill. Students will be given the task to use data science tools and text analysis to screen the resumes.

UNIT THREE

Methods of Research: The Classic Churn Case in Data Science
Essential Question: How do you do predictive modelling and segment data by progressive attribute selection?
  • In this unit, students are tasked with identifying the characteristics of “churning” music students (those that dropped out after 2 months). Neo Avant-Garde (Neo) is a North American private high school for teenage learners working towards entering the first year at the top universities in the world. In recent years, the teaching staff at Neo have noticed students dropping out of the music program.

UNIT FOUR

Implementation and Impacts: International Business Fundamentals
Essential Question: How do businesses stay competitive in the global market using Data Science?
  • In this unit, students will complete a case study that involves mapping Canada’s imports and exports data, illustrating trends in trade volume, and Canada’s trading partners. Students will learn about the different types of graphs available for displaying their data, the pros and cons of each of these graphs as well as bias in graphs.

CULMINATING PROJECT

30% of Final Grade
  • This project is the final evaluation of IDC4U Data Science online. For this project, students will apply any of the concepts they have learned in the course to analyze the data. This project is worth 30% of the final grade.
VIEW COURSE GRADE BOOK
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