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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
Mon, 09/11/2023 Fact SheetInternational Students

Next Start Dates

Monday, September 11, 2023

Tuition & Fees

$15,100: 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.

Click here for more information on Tuition & Fees for International Students.

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

Click here for admission requirements for International Students.

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

Predictive Analytics Diploma applicants must have a minimum of two years of professional work experience in applied computer science, applied statistics, engineering, or a business role involving the use/analysis of data.

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

Applied Statistics for Data Science

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  • Read more about Applied Statistics for Data Science

Big Data Platforms

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  • Read more about Big Data Platforms

Data Acquisition & Management

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  • Read more about Data Acquisition & Management

Database & Programming Essentials

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  • Read more about Database & Programming Essentials

Data Visualization for Analytics

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  • Read more about Data Visualization for Analytics

Effective Oral Communication

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  • Read more about Effective Oral Communication

Effective Written Communication

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  • Read more about Effective Written Communication

Foundations of Data Science

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  • Read more about Foundations of Data Science

Indigenous Insights

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  • Read more about Indigenous Insights

Predictive Analytics Theory & Practice

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  • Read more about Predictive Analytics Theory & Practice

Project in Predictive Analytics

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  • Read more about Project in Predictive Analytics

Project Management Fundamentals

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  • Read more about Project Management Fundamentals

Resume Building & Job Search Techniques

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  • Read more about Resume Building & Job Search Techniques

Topics in Data Science

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  • Read more about Topics in Data Science

Writing for Academic Success

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  • Read more about Writing for Academic Success

Student Life

Find more information on student life at PACE here.

Career Opportunities

  • Data Scientist
  • Data Engineer
  • Quantitative Analyst
  • Qualitative Research Analyst
  • Data Analyst
  • IT Systems Analyst
  • Business Analyst
  • Business Intelligence Analyst/Specialist
  • Data Warehouse Analyst/Developer

Certifications

Academic Credentials

Upon completion of this program students will earn the Predictive Analytics Diploma

The Predictive Analytics Diploma prepares students to seek the follow professional certifications:

  • Certified Analytics Professional (CAP)
    • For more information on obtaining the CAP credential click here.
  • Certified Business Intelligence Professional (CBIP)
    • For more information on obtaining the CBIP Credential click here

Tech Requirements

Students must have a laptop that meets the tech requirements for their program (not included in tuition)
PC hardware
  • CPU: Multicore Intel® or AMD processor (2 GHz or faster processor with SSE 4.2 or later) with 64-bit support.
  • RAM: 8GB of RAM (16GB recommended)
  • Graphics card: 2 GB of VRAM
  • Hard Disk space: 256GB (500GB recommended)
  • Operating system: Microsoft Windows 10 or 11  (64 bit) (versions Windows 10 versions  20H2, 21H1, 21H2, and Windows 11 version 21H2)
Apple hardware
  • Processor: Multicore Intel® processor (2 GHz or faster processor with SSE 4.2 or later) with 64-bit support or Apple silicon/M1
  • Operating system: macOS 12.0 (Monterey), version 11 (big sur) and version 10.15 (Catalina)
  • RAM: 8GB (16GB recommended)
  • Hard disk space: 256GB (500GB SSD recommended)
  • Software to run Virtualization for Microsoft Windows
    • Parallels Desktop or VirtualBox

Additional Comments

Predictive Analytics Industry Memberships

Admittance into the program includes student membership to the following:

  • DAMA International
  • Transforming Data With Intelligence
  • Tech Manitoba

Apply Today
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