Features:

• Some courses may be completed online.
• Complete the program in four semesters full-time, study part-time if you prefer. Incoming international students may qualify for entrance scholarships based on academic performance.

Artificial Intelligence (AI) is a rapidly growing and evolving field, one that is becoming a critical tool in existing and emerging industries — including technology, medicine, entertainment, education, and beyond. 

UFV's AI and Machine Learning post-baccalaureate diploma builds on your degree and gives you the computing, data, and information systems skills employers need as demand for AI and machine learning professionals grows.

This program may be right for you if:

• you already hold a three- or four-year bachelor's degree
• want to build new skills and open up more career options

Go to the program outline for the complete list of required courses and credits. Check the program schedules page for a guide to which courses to take in a given semester.

Go to entrance requirements for the AI and Machine Learning program in the UFV Academic Calendar.

This program is open for international students.

• Learn how to apply as an international student

• Go to all programs open to international students

Students who do not meet the entrance requirements may complete upgrading to meet prerequisites for university-level courses. 

Prospective students should contact the Future Students office to learn more about upgrading options. 

Current or returning students should connect with the appropriate advising area based on the level of upgrading required:  

• University-level upgrading (100 level and above): Qualifying Studies Advisor 

• High school equivalent courses (below 100 level): Upgrading Advisor

1. Use current techniques, skills, and tools necessary for Information Systems and Technology.
2. Analyze the local and global impact of computing on individuals, organizations, society, and Indigenous contexts.
3. Employ interpersonal, teambuilding, and leadership skills to solve problems independently and in diverse teams.
4. Apply ethical considerations in information systems practice.
5. Apply concepts of computing and mathematics appropriate to AI and Machine learning.
6. Employ various platforms and devices to collect and train big data in different business domains.
7. Design user interfaces to improve human–AI interaction and real-time decision-making.
8. Create an optimal solution using AI, data mining, and machine learning tools for complex problems.