Predictive Analytics Post-Degree Diploma
Programs Page
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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.
This program is PGWP-eligible under CIP Codes: 30.7101 Data analytics, general; 30.7103 Data visualization
Limited Time Exclusive Tuition Benefit for PACE Student Spouses
Spouses of PACE students have the unique opportunity to enroll in a full-time PACE program at the Canadian Domestic Tuition Rate. To qualify, proof of marriage or common-law partnership is required, and the spouse’s program must begin within one year of the first.
For two-year programs, the discounted rate applies to the first year only. Please note that full international tuition must be paid upfront, with the difference refunded after the program begins.
Take advantage of this exceptional opportunity to advance your education while your partner studies at PACE. Contact us today to learn more!
International
In-Class
Application Deadlines
When Should I Apply?
Applications open one year before the next program start date.
We strongly advise applicants to apply early as space is limited and demand for full-time programs is extremely high.
Key Application Deadline
- May 15
NOTE: This program may reach capacity prior to application deadline.
*Note if you do not see the program listed for the intake you are interested in on the online application portal, we have reached capacity and are no longer accepting applications.
Tuition & Fees
$19,850: Tuition cost includes a mandatory UWSA and health insurance 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 reguarding 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.
Hybrid Program
This program follows a blended learning model, combining in-class sessions, live online instruction, and scheduled online coursework to create a dynamic and adaptable educational experience.
Courses are carefully structured to balance in-person interaction with the convenience of online learning. Live online sessions allow students to engage with instructors and classmates in real-time, while scheduled online coursework provides flexibility in when they complete assignments within set deadlines. The number and format of online courses may vary based on program needs and scheduling.
This multi-modal approach ensures that students stay connected with their peers and instructors while developing essential workplace skills such as digital collaboration, adaptability, accountability, and effective communication. While students must follow the program’s set schedule, this blended format allows them to engage with learning in different ways, whether attending classes on campus, participating in live online discussions, or completing coursework independently.
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 on 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 can:
- 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
- International students are required to hold a minimum of an undergraduate degree or a 2-year diploma. (Applicants with a 2-year diploma must have one additional year of work experience to be eligible.)
- Undergraduate degree in Computer Science or Computer Engineering Degree within last five years
- Must include courses in Python and SQL
OR
- Undergradute degree in Business, Engineering, Mathematics, Statistics, Physics or related degree AND minimum 1 year of work experience within the last five years using Python and SQL. Additional work experience in Java and XML is preferred.
- Undergraduate degree in Computer Science or Computer Engineering Degree within last five years
- A Higher National Diploma from Nigeria and Ghana are exceptions
- Advanced programming knowledge is strongly recommended.
- The Cumulative Grade Point Average (GPA) or Final Percentage on these transcripts will be assessed for eligibility.
- If a higher degree is attained (post-graduate diploma, Master’s, or PhD) the minimum GPA or Percentage must be attained in all degrees.
- 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 .
For complete admission details by country, please visit our detailed Admission Requirements for international students.
Work Experience
- If applicant has completed an IT degree, with courses including Python, JSON, SQL, within the last two years, no work experience is required.
- For all other applicants, a Bachelor’s degree is required AND minimum 1 year of work experience within the last five years using Python and SQL. If holding a 2-year Diploma: A minimum of 2 years of work experience (internship placements and practicum experience will be counted as experience).
- 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.
|
Test |
Score |
|
Duolingo |
Overall score: minimum 120 |
|
IELTS Academic |
6.5 |
|
TOEFL iBT or TOEFL MyBestScore |
86 |
|
Heartland International English School |
80% |
|
International Language Academy of Canada |
3.4 |
The University reserves the right to request English language proficiency testing result documentation for any international applicant.
Download the UWPACE English Language Requirements (PDF) for additional English proficiency tests and programs and waiver options for the English language requirement.
Courses & Descriptions
Career Opportunities
Certifications
Academic Credentials
On successful completion of the full-time program, you will be eligible for the following academic credentials:
- Predictive Analytics Post-Degree Diploma
Industry Credentials
The Predictive Analytics Post-Degree 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).
⚠️ Tablets are not recommended for use in any program. Some required software may not be fully compatible with tablets, particularly Android devices. Students should ensure they have access to a laptop that meets the specifications below.
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
Mahesh Kumar Batti Venkata Naga
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Predictive Analytics Industry Memberships
Admittance into the program includes student membership to the following associations: