Note: This is the 2019鈥�2020 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .
Program Requirements
This program is designed to provide the fundamentals of digital media, digital analytics and data science technology so as to prepare students for careers in the increasingly important and in-demand fields of digital analytics, business intelligence and data analytics. The program objective is to use data to improve digital media, predict future trends, transform customer experiences, improve productivity, and guide business decision making. As such, students will be uniquely equipped with the deep analytical skills integral to business today.
Corequisite Course (3 credits)
-
CMS2 500 Mathematics for Management (3 credits)
Overview
Management Science (CCE) : Basic mathematics needed for business applications, including graphs of functions, series summation, mathematics of finance, annuity, discounted cash flow, internal rate of return, permutations, combinations, maxima and minima of functions with business applications in optimization, introductory statistics and probability
Terms: Fall 2019, Winter 2020, Summer 2020
Instructors: Golovina, Galina (Fall) Kelome, Djivede (Winter) Abdenbi, Brahim (Summer)
Prerequisite: CMSC 000
Note: "Mathematics for Management" must be completed in the first semester of the Diploma in Management program.
Required Courses (30 credits)
-
CCS2 505 Programming for Data Science
(3 credits)
Overview
Computer Science (CCE) : Tools and techniques for designing and implementing software applications by using modern programming languages relevant to data science.
Terms: Fall 2019
Instructors: Yu, Tzu-Yang (Fall)
-
CMIS 530 Digital Analytics and Targeting (3 credits)
Overview
Management Information Systems : Covers fundamental techniques in measuring and analysing the digital marketing experience success and effectiveness as well as using audience data to improve advertising and content using targeting and experiments. How to measure, analyze, and act upon the evolving internet technologies and trends.
Terms: Fall 2019
Instructors: Harrisson-Boudreau, Jean-Philippe (Fall)
-
CMIS 543 Digital Customer Experience (3 credits)
Overview
Management Information Systems : Covers the fundamental techniques for understanding, analyzing and optimizing customer experience on digital platforms. Explores best practices in designing and optimizing conversion actions in an online business. Management of customer data and confidentiality.
Terms: Winter 2020
Instructors: Mottaghi, Hoda (Winter)
-
CMIS 544 Digital Marketing Automation, Planning and Technology (3 credits)
Overview
Management Information Systems : Covers the fundamental concepts needed to develop a digital marketing plan. Enables students to gain an understanding of market behaviour, translation of corporate goals into digital marketing objectives, basic overview of various strategic approaches to align to objectives, as well as implementation and control.
Terms: Winter 2020
Instructors: Muscott, Adam (Winter)
-
CMIS 545 Cloud Computing Architecture (3 credits)
Overview
Management Information Systems : Covers different cloud infrastructures and architectures in the context of deployed cloud computing systems that are appropriate for different businesses. Enables students to use key business metrics to make decisions on the suitability of applications for cloud deployment.
Terms: Fall 2019
Instructors: Havas, Michael (Fall)
-
CMIS 549 Digital Media and Search Engine Optimization (3 credits)
Overview
Management Information Systems : Covers the fundamentals of promoting a brand through digital mediums and how to take advantage of earned digital media. Provides an understanding of how paid search, search engine optimization, various forms of digital media planning and placement, social media promotion work and, how to monitor and optimize performance.
Terms: Fall 2019
Instructors: Harrisson-Boudreau, Jean-Philippe (Fall)
-
CMIS 550 Fundamentals of Big Data (3 credits)
Overview
Management Information Systems : Investigates big data鈥檚 enabling technologies; compares big data to traditional data models; and explores how big data enables applications such as data mining and deep learning.
Terms: Winter 2020
Instructors: Havas, Michael (Winter)
-
CMS2 505 Quantitative Analysis Tools in Decision Making (3 credits)
Overview
Management Science (CCE) : This course provides applications-oriented operations research modeling tools, such as: linear programming, integer programming, network modeling, and queuing theory. Use of spreadsheet/modeling software is an integral part of this course.
Terms: Fall 2019
Instructors: Troy, Philip (Fall)
Corequisite: CMS2 500
-
CMS2 527 Business Intelligence and Analytics (3 credits)
Overview
Management Science (CCE) : This course provides a managerial and technical focus on computational and business techniques which can help to identify new business opportunities and transform an organization鈥檚 future by optimizing operational and strategic decision making.
Terms: Winter 2020
Instructors: Troy, Philip (Winter)
Prerequisite(s): CMS2 500
-
CMS2 529 Introduction to Data Analytics (3 credits)
Overview
Management Science (CCE) : Focuses on executing statistical methods on data sets for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results in support of business decision making.
Terms: This course is not scheduled for the 2019-2020 academic year.
Instructors: There are no professors associated with this course for the 2019-2020 academic year.
Prerequisite: CMS2 500
