Traits, skills and aptitudes
Those working in the artificial intelligence field tend to be innovative, objective and directive.
You need:
- analytical skills
- technical aptitude
- effective communication skills
- ethical awareness
- an inquiring and inventive mind
- an eye for details
- patience and an organized approach to troubleshooting
- decision-making and problem-solving skills
- business acumen
- an aptitude for math and science
- teaching skills
- time-management skills.
To do well in this field, you should enjoy being innovative, working with others or independently, and being precise in your work.
Practicum, co-op and work integrated learning opportunities
You’ll complete a capstone project where you’ll address a real-world AI challenge in a safe-to-fail environment.
You can also complete an optional co-op work term after semester two.
Specialized intakes
This program is available to international applicants as a stand-alone program or as part of a program bundle - two programs delivered consecutively.
For details on available bundles including this program, see international bundle programs.
Credential
Upon successful completion of this program, you’ll receive a SAIT Integrated Artificial Intelligence post-diploma certificate.
Accepts international applicants - PGWP-eligible
This program accepts international applicants and meets the eligibility criteria for the Post-Graduation Work Permit program, as long as the student is registered in on-campus classes or completes more than 50% of the courses on campus (for blended options).
International students attending all classes online will NOT be eligible for a Post-Graduate Work Permit. International students are responsible for maintaining their eligibility throughout their studies.
Related careers
Our graduates may work in the following occupations. Some careers require additional experience and education.
Potential careers (NOC):
- Data scientists (21211)
- Cybersecurity specialists (21220)
- Information systems specialists (21222)
- Business systems specialists (21221)
- Software developers and programmers (21232)
- Software engineers and designers (21231)
- Computer engineers (except software engineers and designers) (21311)
Admission requirements - Applicants educated in Canada
Applicants must demonstrate English language proficiency and completion of the following courses or equivalents:
- a diploma or degree from an accredited post-secondary institution in one of the following subject matter areas with a minimum cumulative GPA of 2.3 (67% or C+)
- Information Technology
- Computer Science
- Data Analytics
- Software Development
A combination of education and professional experience may be considered in place of the above at the discretion of the Academic Chair.
Program outline
The Integrated Artificial Intelligence post-diploma certificate requires 30 credits (10 courses) to complete, plus an optional cooperative work term.
The program spans two 15-week semesters, followed by the optional cooperative work term.
Suggested schedule of study
Co-op work term (Optional)
Progression
You must attain a PGPA and/or a CGPA of 2.0 or better each semester and pass the prerequisite courses to progress through the program.
To qualify for graduation, you must pass all courses, attain a CGPA of 2.0 or better and complete course requirements within the prescribed timelines.
Review our grading and progression procedure >
Books and supplies
Books and supplies are approximately $1,500 per full-time year. The required textbooks will be discussed in class.
This is a bring-your-own-device program with custom computer hardware and software requirements.
PC minimum requirements
- i7 processor
- 32 GB RAM
- 512 GB SSD storage
- Nvidia Quadro T1000 video card
- 15” screen size
- 1920x1080 screen resolution
- Windows 10 Pro 64-bit operating system
Suggested model: Lenovo ThinkPad P1 Gen 3
Approximate cost: $3,000
Required equipment/tools
You may require a cloud computing service subscription to CloudMyLab, approximately $800 - $1,200 per year.
Program outcomes
- Governance: explain the ethical considerations and their application in AI systems deployment, management, and integration within organizations.
- Data management: apply knowledge of cloud computing and data management for AI.
- Emerging trends: examine emerging trends and developments in AI operations and integration.
- Analytics: apply advanced data science and data analytics concepts to existing data sets to create models.
- Solutions: apply appropriate AI technology solutions to various domains, based on an organizational context.
- Processes: interpret how AI systems impact business processes and decision-making.
- Communication: implement data visualization and communication strategies to clearly demonstrate the impacts of AI systems.
- Design: design AI infrastructure solutions.
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