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Artificial Intelligence Diploma

Programs Page

Be on the cutting edge of innovation with a diploma in AI and machine learning. Artificial intelligence and machine learning is a branch of data science growing at full speed. We see the application of artificial intelligence in our daily lives, from checking the weather forecast to social media feeds, from banking and finance to healthcare, amongst others.

In this program, graduates master the skills to create and use problem-solving algorithms to provide insights, predictions, and operationalization strategies needed to transform any organization into an innovative, efficient, and sustainable company of the future.

Domestic
In-Class
Tue, 01/13/2026 Fact SheetInternational Students

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, days and hours vary and classes may be scheduled during the day time or evenings from 9AM to 9PM.

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 artificial intelligence is common place on devices ranging from personal smartphones to large industrial equipment. From simple algorithms to complex decision making, this program ensures that graduates have a firm, applied knowledge of artificial intelligence and machine learning.  While the curriculum and learning outcomes include establishing a general understanding of the theories underlying AI, greater emphasis is placed on the application of these techniques in a practical setting.

Successful graduates of this program shall be able to:
  • Design and implement data acquisition, management, and cleansing solutions to support data science applications;
  • Use statistical techniques in the development of data science applications;
  • Describe legal, ethical, and societal considerations arising from the application of data science and artificial intelligence;
  • Identify suitable applications and recommend the use of AI within an organization;
  • Design the overall solution architecture required to support AI; and
  • Design, test, and implement applied AI solutions.

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 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

AI & Machine Learning Theory & Practice

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  • Read more about AI & Machine Learning Theory & Practice

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 for Data Science

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  • Read more about Data Acquisition & Management for Data Science

Database & Programming Essentials for Data Science

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  • Read more about Database & Programming Essentials for Data Science

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

Introduction to Machine Learning

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  • Read more about Introduction to Machine Learning

Project in AI & Machine Learning

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  • Read more about Project in AI & Machine Learning

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

Generative AI in the Workplace

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  • Read more about Generative AI in the Workplace

Business Fundamentals

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  • Read more about Business Fundamentals

Student Life

Find more information on student life at PACE here.

Career Opportunities

  • Data Scientist
  • AI Programmer/Specialist/Engineer
  • Machine Learning Engineer/Specialist
  • Machine Learning and AI Developer
  • AI/ML Researcher
  • AI/ML Data Architect
  • Deep Learning Engineer

Certifications

Upon completion of this program students will earn the Artifical Intelligence Diploma.

The Artificial Intelligence Diploma prepares students to seek certification as an Artificial Intelligence Engineer (AIETM) through ARTiBA, the Artificial Intelligence Board of America.

For more information on obtaining the AIE Credential click here.

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

Artificial Intelligence Industry Memberships

Admittance into the program includes student membership to the following:

  • Canadian Artificial Intelligence Association
  • Tech Manitoba

Student Success Story

Gisela Sanchez
Artificial Intelligence Diploma
Read More

Apply Today
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