University of Toronto

Overview

The Focus in Data Analytics at the University of Toronto is designed to equip students with advanced and practical skills in applied economic analysis. This program emphasizes hands-on experience with real-world datasets, utilizing programming and statistical tools to address critical questions in economics and policy-making.

What you'll study

Programme Structure

The curriculum is centered around a combination of core analytics and economics courses, alongside practical training involving datasets and software applications. The availability of specific courses may vary by term.

• Computer Programming
• Computer Science
• Geographic Information and Mapping
• Big-Data Tools for Economists
• Data Analysis and Applied Econometrics in Practice
• Labour Economics: The Distribution of Earnings
• Empirical Macroeconomics and Policy

Applied skills you develop

• Programming-based data workflows, including proficiency in Python
• Econometric and statistical analysis tailored to economic inquiries
• Data visualization and interpretation of empirical findings
• Utilization of analytics tools in research and policy contexts

Capstone/thesis

While a specific thesis or capstone requirement is not detailed, any capstone or research project necessary for your track will be outlined in the official course plan.

Entry requirements

There are no specific GRE, GMAT, or GPA grading score requirements publicly disclosed for this program. Prospective students should review the official University of Toronto resources for the most current admission prerequisites.

Career prospects

Graduates of the Focus in Data Analytics program are well-prepared for a variety of roles in data analysis, economic consulting, policy development, and research. The skills acquired throughout the program enable students to effectively analyze data and contribute valuable insights in both private and public sectors, making them competitive candidates in the job market.