Data Science Foundations Microcredential

Develop skills aligned with current industry and research practices and build core computational and statistical skills for working with data across applied and research contexts.

Data Science Foundations introduces essential tools and concepts used in data science, with a focus on developing practical skills in data analysis, modeling, and reproducible workflows.

Whether you are new to data sciences or looking to strengthen your data science fundamentals, this microcredential provides a focused entry point to prepare for more advanced AI deployment and/or machine learning training.

What you'll learn:

  • Build proficiency in the Unix shell, Git and GitHub, Python, and SQL
  • Learn foundational statistical methods for regression, classification, and resampling that are foundational for modelling to find patterns and make predictions
  • Gain hands-on experience through applied exercises and case studies using real-world datasets.
Learners receive a University of Toronto Data Sciences Institute–branded microcredential that can be listed on a résumé or LinkedIn profile.

Length

8-weeks

Cost

$1,599

Format

Live online, synchronous

Next session

April 6 – May 29, 2026

Certificates

The Data Science Foundations microcredential can be combined with the Machine Learning Foundations microcredential to form the Data Science and Machine Learning Certificate, or with the Deploying AI microcredential to form the Data Science and Deploying AI Certificate 

Content and Skills Developed

Gain essential technical skills for data science through our engaging online instructor-led webinars. This microcredential includes four modules delivered over 8 weeks and features two case study presentations led by industry experts—one focused on SQL and one on Python. You’ll see how these skills are applied in real-world settings, gaining insights into professional workflows, challenges, and best practices.

  • Unix Shell & Git
    This module provides a foundational understanding of Unix shell, Git version control, with an emphasis on reproducibility principles. Participants gain proficiency in shell commands, file navigation, Git repositories, and collaborative workflows.
  • Python
    Get started with Python, one of the most widely used languages in data science. You’ll learn the basics of writing and reading code, including how to use functions and structure your work so it’s clear and reusable.
  • SQL
    Learn how to work with data stored in databases. This module covers how to find, filter, and combine data using SQL, as well as how databases are structured. You’ll also be introduced to responsible data use and privacy considerations.
  • Linear Regression, Classification, and Resampling
    Learn how data scientists use models to find patterns and make predictions. You’ll build simple regression and classification models, learn how to test how well they work, and explore how results are interpreted and used responsibly in real-world decisions.

FAQ

The Data Sciences Institute is a University of Toronto hub and incubator for data science research, training, and partnerships. The DSI’s mission is to provide leadership and capacity to catalyze the transformative nature of data sciences across a broad range of disciplines. 

Data Science Foundations is designed for learners from diverse backgrounds who want to build foundational data science skills. No prior programming or data science experience is required. Learners may include professionals from academia, industry, government, or non-profit sectors seeking practical, in-demand data skills.

This offering supports individuals who are new to data science, as well as those looking to formalize or strengthen existing skills. The curriculum provides value to beginners while also enhancing analytical and computational capabilities for applied projects and real-world contexts.

It is particularly useful for learners who want to explore AI and machine learning but need a strong foundation first, equipping participants with the essential skills required to progress confidently to advanced AI and ML learning pathways.

There are no formal pre-requisites for this microcredential. This microcredential is designed to support learners who are new to the data science, with concepts and tools introduced from the ground up.

Basic comfort using a computer and an interest in working with data will help you get the most out of the microcredential.

This microcredential provides a structured and accessible entry point into data science, focusing on practical skills that are widely used across industries and research settings. Learners gain hands-on experience with core tools and statistical methods that form the foundation of modern data analysis.

Through applied exercises and case studies, learners develop the confidence to work with real-world data and build a strong base for continued learning in machine learning and advanced analytics. The microcredential also offers a flexible way to upskill, strengthen your résumé, and earn a University of Toronto Data Sciences Institute–branded credential that can be stacked toward the Data Science and Machine Learning Certificate or the Data Science and Deploying AI Certificate.

Yes, upon completion of this microcredential, you will have the skills needed to take Deploying AI and Machine Learning microcredentials.

Learners who complete both the Data Science Foundations microcredential and the Machine Learning Foundations or Deploying AI microcredential are eligible to receive the Data Science and Machine Learning Certificate or Data Science and Deploying AI Certificate.

The microcredential modules are offered live, online over an eight-week period.

Sessions are held three days per week for 2.5 hours per day (Tuesday–Thursday, 6:00–8:30 PM). Optional support and facilitated work periods with learning support staff are available for half an hour before and after each class, as well as Fridays from 1:00–2:30 PM. During these sessions, participants can ask questions and receive help with assignments; no new material is introduced.

This microcredential features applied case studies in SQL and Python, giving participants hands-on experience working with real-world datasets. These case studies provide practical insight into common data analysis workflows and help bridge the gap between foundational concepts and applied data science practice.

Evaluation: Completion of this microcredential is evaluated based on successful completion of assignments and achievement of the learning outcomes.

Participants must attend synchronous sessions for about 7.5 hours per week over eight weeks. Sessions include homework and assessments designed to help you apply newly learned skills and demonstrate your understanding.

Full engagement is essential because new topics are introduced each week, and timely completion of assessments ensures you keep pace with the course.

A recording can be made available to you upon request.

U of T staff may be eligible to apply for the Staff Tuition Waiver for this microcredential, depending on their employee group and how the learning relates to their role. For details and the application form, please see the central tuition waiver information and consult with your manager and HR.

Waiver forms are available through the People Strategy, Equity & Culture website. Please note that the application process is managed by your divisional HR office. Interested staff should use the existing Staff Tuition Waiver form and include a link to the Data Science Foundations webpage and the registration fee (pre-tax). Central Benefits will determine eligibility and the amount that can be covered on an individual basis.  If approved, you will be provided guidance on the payment process and recording microcredential completion.

Learn more and access the form here.

Yes, U of T postdoctoral fellows can register for Data Science Foundations.

Postdoctoral fellows can explore funding support through the School of Graduate Studies Professional Development Reimbursement for Postdoctoral Fellows . Please contact your unit’s HR representative for guidance.

Within four to six weeks of successful completion, you will receive your microcredential badge indicating achievement of the outlined learning outcomes and competencies. Microcredentials are tamper-proof, verifiable, blockchain-based, and 100% digital, and can be included on your résumé and shared on social media platforms such as LinkedIn and Facebook.

Learners who complete both the Data Science Foundations microcredential and the Machine Learning Foundations or Deploying AI microcredential are eligible to receive the Data Science and Machine Learning Certificate or Data Science and Deploying AI Certificate. Learners who have completed a full DSI certificate may email the DSI team to request a certificate request form. Once submitted, the certificate will be issued electronically as a PDF via email.

Participants may withdraw from the microcredential at any time by requesting withdrawal via email.

  • Refunds are eligible only if the withdrawal request is received at least twenty-five (25) working days before the start date.
  • Refunds are issued to the original payee via the original method of payment. Please include your payment receipt when requesting a refund.
  • Refunds are subject to a $75 CAD administrative charge per microcredential.
  • No refunds are possible if your request is submitted less than twenty-five (25) working days before the start date.
  • Requests to defer enrolment will not be accommodated.

All cancellation requests must be sent by email to courses.dsi@utoronto.ca.

Yes. Participants receive the T2202 Tuition and Enrolment Certificate. T2202 forms are issued based on the year the microcredential is completed—not the year when payment was made.