Last updated on 2025-04-24
Program Overview
The Master of Applied Science in Data Science, Analytics, and Artificial Intelligence (DSAAI) is designed to provide students with a comprehensive understanding of the technical aspects of data science. This program is a natural extension of the popular Collaborative Specialization in Data Science, focusing on interdisciplinary approaches. Students will engage in groundbreaking research across various methodologies, including statistics, AI methods, and software engineering. The program emphasizes the collection, preprocessing, exploration, and visualization of data from diverse sources, preparing graduates for a dynamic career in data science and analytics.
Program Structure
The Master of Applied Science in Data Science, Analytics, and Artificial Intelligence is structured to be completed in 2 years. The program offers various pathways, including:
- Coursework
- Research Project
- Thesis (depending on program)
Students will benefit from a co-op option, allowing them to gain practical experience in the field. The program is offered in the Fall term, with an application deadline of February 1. This unique program spans four academic units, providing a wide disciplinary breadth and multiple perspectives on data science.
Featured Experiences
- Co-op opportunities to gain real-world experience in data science.
- Interdisciplinary approach, combining insights from the Faculty of Science and Faculty of Engineering and Design.
- Groundbreaking research opportunities in various areas of data science, including data mining, predictive analytics, and machine learning.
- Access to advanced data analytics platforms and parallel processing techniques.
Career Options
Graduates of the Master of Applied Science in Data Science, Analytics, and Artificial Intelligence can pursue a variety of career paths in Canada, including:
- Data Scientist: Analyze complex data sets to extract meaningful insights and inform business decisions.
- Data Analyst: Utilize statistical tools to interpret data and provide actionable recommendations.
- Machine Learning Engineer: Develop algorithms that enable machines to learn from data and improve their performance over time.
- Business Intelligence Analyst: Transform data into strategic insights to drive business growth and efficiency.
- Data Engineer: Design and maintain the architecture that allows for the collection and processing of data.
DISCLAIMER: The information above is subject to change. For the latest updates, please contact LOA Portal's advisors.
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