FULL-TIME | WINNIPEG LOCATIONS ADSAF-DP Applied Data Science and Artificial Intelligence

• Two year diploma program (delivered over four terms)
• September and January intake options
• Exchange District Campus, Winnipeg
• Mandatory Work Integrated Learning (WIL) term (Co-op Work Experience or Industry Project)
• Spring terms are normally scheduled breaks with no classes. However, Work Integrated Learning (WIL) may occur during this period, and a limited number of courses may be offered based on student needs and at the discretion of the program.
• Classes typically run between 8:00 a.m. and 6:00 p.m. (please note that some classes may occasionally run later in the evening)
• Courses are delivered in a blended format, typically 50% on campus and 50% online/remote (the schedule may be updated periodically and will be communicated in advance)
• Students are required to provide their own laptop that meets the program’s technical requirements 
• International applicants please visit Academic Program, Dates and Fees for a listing of programs for international students, current availability and online application instructions.

Description:

Recent advances in artificial intelligence, machine learning, and computing power have accelerated the use of data-driven technologies across industries such as healthcare, finance, agriculture, manufacturing, and government. Organizations increasingly rely on professionals who can transform data into insight and build intelligent systems that support better decisions and automation.

In the Applied Data Science and Artificial Intelligence program, students develop the technical and analytical skills needed to design and implement practical AI and data solutions. Through hands-on learning, students build a strong foundation in programming, mathematics, analytics, and machine learning while working with modern AI tools, automation techniques, and generative AI systems. The program also emphasizes responsible and secure AI development, including privacy-aware design, data governance, and ethical deployment of AI systems.

In this program, you will:

• Study the mathematical, statistical, and computational foundations that enable data science, machine learning and artificial intelligence.
• Learn to collect, manage, and analyze data using modern data management, database, and data architecture techniques.
• Design and implement machine learning models, including supervised learning, unsupervised learning, and deep learning.
• Work with applied AI tools, automation technologies, and intelligent systems to solve real-world problems.
• Develop privacy-aware and secure AI systems using modern tools and best practices for data protection and responsible AI.
• Strengthen essential employability skills such as communication and collaboration and learn to explain technical ideas to both technical and non-technical audiences.
• Gain practical experience working on real-world problems through applied projects and industry-informed learning.

Graduate Profile:

Graduates of the Applied Data Science and Artificial Intelligence program are prepared to:

• Analyze real-world problems and determine appropriate data science, machine learning, or artificial intelligence solutions based on the problem domain, available data, and desired outcomes.
• Develop software solutions using appropriate programming languages, tools, and frameworks to support data analysis, machine learning, and AI applications.
• Conduct research by reviewing technical literature, collaborating with stakeholders, and applying investigative methods to acquire domain knowledge and evaluate existing approaches.
• Prepare, manage, and structure data for analysis by applying data cleaning, transformation, and data management practices to support reliable and meaningful insights.
• Design, train, and evaluate machine learning models—including supervised, unsupervised, and deep learning approaches—to generate accurate and reliable predictions from data.
• Develop intelligent applications and automated systems that integrate data science, artificial intelligence, and software development practices.
• Verify and validate software and AI systems to ensure they meet requirements, perform reliably, and achieve their intended outcomes.
• Communicate technical concepts, results, and processes effectively to both technical and non-technical audiences using written, verbal, and visual communication methods.
• Apply responsible and ethical practices in the development and use of data and AI systems, including attention to privacy, security, and regulatory requirements.
• Demonstrate professionalism, integrity, accountability, and a commitment to continuous learning in a rapidly evolving technology field.