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Predictive Analytics Diploma
Programs Page
Stay ahead of the competition with this cutting-edge applied program focused on harnessing big data for smart business decisions that optimize competitive and social benefits within an organization. Graduates of this program master a range of analytical models to become strategic leaders in any industry.
Domestic
In-Class
Tuition & Fees
$13,100: Tuition cost includes the $100.00 UWSA Fee. Costs are tentative.
$1,000-$1,500: Textbook costs may vary depending on new, rental, used, or electronic purchasing choices. Textbooks are a requirement
For more information regarding tuition & fees and payment options, click here.
Duration
12 months in duration, Mon-Fri, hours may vary.
Two breaks of one week throughout the program and two weeks off for winter break.
Objectives & Outcomes
The use of large volumes of data to forecast and predict human behaviour, business, and socio-economic outcomes has accelerated rapidly in recent years. This program builds foundational skills in data science with a specialization in the use of predictive models to forecast outcomes. Students will learn to apply data science and predictive modelling to provide insights, predictions, and operationalize the use of data for competitive and social benefits within an organization.
Successful graduates of this program shall be able to:
- Design and implement data acquisition, management, and cleansing solutions to support data science applications;
- Use effective visualizations to communicate patterns, trends, and other findings stemming from the analysis of data;
- Use statistical techniques in the development of data science applications;
- Describe legal, ethical, and societal considerations arising from the application of data science and predictive analytics;
- Identify suitable applications and recommend the use of predictive analytical models in a business context;
- Design the overall solution architecture required to support predictive modeling applications; and
- Design, test, and implement predictive analytical models.
Admission Requirements
Academic Requirements
a. Undergraduate degree or college diploma in Business, Computer Science, Engineering, Mathematics, Statistics, or Physics
or
b. In lieu of a degree/diploma; significant work experience involving analysis of data in an organizational or applied research context may be considered on an exceptional basis
Programming knowledge is strongly recommended.
Work Experience
-
Applicants who have completed an IT degree or college diploma within the past two years, with coursework in Python, JSON, and SQL, are not required to have work experience.
-
For applicants without a related degree, a minimum of one year of work experience within the last five years is required using Python and SQL. Additional work experience in Java and XML is preferred.
English Language Requirements
Applicants whose previous education was completed outside of Canada and where English may or may not have been the medium of instruction, must submit proof of meeting one of the accepted English language proficiency measures.
Download the UWPACE English Language Requirements (PDF) for additional English proficiency tests and programs and waiver options for the English language requirement.
International Students
Please visit our detailed Admission Requirements for international students.
The University reserves the right to request English language proficiency testing result documentation for any international applicant.
Courses & Descriptions
Student Life
Find more information on student life at PACE here.
Career Opportunities
Certifications
Academic Credentials
Upon completion of this program students will earn the Predictive Analytics Diploma
The Predictive Analytics Diploma prepares students to seek the following professional certifications:
- Certified Analytics Professional (CAP)
- Certified Business Intelligence Professional (CBIP)
Tech Requirements
Students must have a laptop that meets the following requirements for their program (not included in tuition).
PC hardware
- OS: Windows 11 (64 Bit) Pro or Home version (Windows 10 would be accepted).
Note: Windows should be up to date (e.g. 23-24H2) - Processor: 12th Gen Intel core i5+
- Graphics: A strong graphics card is recommended for IT and programs that require multimedia design (e.g., NVIDIA GeForce technology); for other programs, an Intel graphics card (e.g., Intel Iris Xe Graphics) is recommended.
- Memory (RAM): 16+ GB, DDR4+.
- Hard Drive: 500+ GB, M.2, PCIe NVMe, SSD.
- Connectivity: Intel Wi-Fi 5-6 AX201, 2x2, 802.11ax, Bluetooth wireless card, HDMI, USB type A and Type C.
- Should include an HD (720P+) webcam for Zoom classes.
Apple hardware
- MacOS: Ventura or later
- Processor: Apple’s M1, M2 or M3 chip with at least 8 Core CPU.
- Graphics: 10 core GPU.
- Memory (RAM): 16+ GB.
- Hard Drive: 500+ GB, SSD.
- Should include FaceTime HD (720P+) webcam for zoom classes.
- Software to run Virtualization for Microsoft Windows:
- Parallels Desktop or Virtual box
Additional Comments
Student Success Story
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Predictive Analytics Industry Memberships
Admittance into the program includes student membership to the following: