Carleton University

Overview

The Data Science, Analytics, and Artificial Intelligence (DSAAI) program at Carleton University is designed to equip students with advanced skills in data mining, machine learning, and analytics. This graduate program emphasizes the design and evaluation of data-driven methodologies, offering students the chance to engage in research across various domains, including statistics, artificial intelligence, and software engineering.

What You'll Study

DSAAI focuses on advanced methods for extracting insights from data.

• Data Mining & Pattern Discovery: Learn techniques to uncover meaningful structures in complex datasets and convert them into actionable information.
• Predictive Analytics & Statistical Modelling: Develop methods for forecasting and assessing the likelihood of future outcomes based on historical data.
• Machine Learning & AI Methods: Explore learning algorithms for large-scale data, covering model training, validation, and performance analysis.
• Analytics for Stored and Streaming Data: Gain proficiency in handling both real-time data and traditional data repositories.
• Scalable Analytics & Parallel Processing: Understand tools and strategies to enhance efficiency when managing large datasets and compute-intensive tasks.

Research and/or Capstone Component: Depending on your degree pathway, you may complete a research-focused requirement, such as a thesis or dissertation, under faculty supervision, aligned with your research interests.

Entry Requirements

Specific GRE or GMAT requirements for this program are not listed. Additionally, GPA requirements are not explicitly mentioned. Applicants are typically required to submit transcripts, a CV or resume, a statement of intent, and two letters of reference.

Career Prospects

Graduates of the DSAAI program will be well-prepared to pursue a variety of career paths in the rapidly growing fields of data science, analytics, and artificial intelligence. Opportunities may include roles in data analysis, machine learning engineering, AI research, and data-driven decision-making across diverse industries.