Predictive Analytics

Description: This course focuses on career management skills needed to navigate the evolving workplace. Students will evaluate their skills, attitudes, and expectations within their chosen careers and explore emerging trends in the workplace. Students will refine their networking strategies and create marketing documents to position them for success. Mock interviews will provide the opportunity for practice, feedback, and reflection as students prepare for future interviews. Students will explore communication strategies that support workplace success and advancement. By the end of this course, students will have created a personalized career management plan.

• Hours: 28
• Credits: 2
• Pre-Requisites:
• CoRequisites:
• Estimated required text and/or learning resource costs: $10.55

Description: In this course, students will enhance their understanding of leadership and management approaches in Canadian organizations. Emphasis on developing effective management strategies including, professional communication, planning, decision making, conflict resolution, effective team building and navigating change. Key concepts include professionalism, adaptability, boundaries and resourcefulness.

• Hours: 42
• Credits: 3
• Pre-Requisites:
• CoRequisites:
• Estimated required text and/or learning resource costs: No cost.

Description:

Using analytical software and programming, students will learn to delve into data sets and draw conclusions using exploratory analytics, predictive and statistical techniques. Including confidence intervals, t-tests, and statistical inference. Students will also practice visualizing their findings in a way that will effectively communicate their conclusions to business stakeholders.

• Hours: 56
• Credits: 4
• Pre-Requisites:
• CoRequisites:
• Estimated required text and/or learning resource costs: $63.00

Description:

This course will build on the predictive analytics tool kit by utilizing both supervised (dependent variable) and unsupervised (no dependent variable) learning methods to uncover the information from the data and then act on this information. Building models such as Classification and Regression (supervised) as well as Clustering (unsupervised) will be covered. Students will apply data modelling techniques using Microsoft Excel.

• Hours: 42
• Credits: 3
• Pre-Requisites:
• CoRequisites:
• Estimated required text and/or learning resource costs: $72.00

Description:

This course will apply the principles of time series analysis to teach students to analyze data where multiple measurements are made over time using common statistical forecasting techniques. Students will study the key concepts, patterns, and relationships found in time series data. Emphasis will be placed on forecasting and predictive analysis.

• Hours: 56
• Credits: 4
• Pre-Requisites:
• CoRequisites:
• Estimated required text and/or learning resource costs: No cost.

Description:

This course builds on the skills developed in Statistical Applications for Data Analytics I to further explore data analytics using current industry tools and best practices. Students will learn to use common industry tools and practices to analyze and interpret analytical models and results to facilitate decision making and generate visualizations. Practical applications of descriptive, predictive, and prescriptive data mining and analysis will be explored across a broad range of industries.

• Hours: 56
• Credits: 4
• Pre-Requisites:
• CoRequisites:
• Estimated required text and/or learning resource costs: $96.00