Key Capabilities in Data Science

The UBC Certificate in Key Capabilities in Data Science focuses on fundamental concepts and practical tech skills to help you solve real-life problems using data. Apply your data science learning in your current role or leverage it for new career or educational opportunities.

By the end of this program, you’ll be able to:

• Understand what data science is and how its principles can be used in a variety of settings
• Perform transparent and reproducible data analysis
• Apply data science techniques in a range of sectors
• Engage in project-based learning that helps you apply and test your knowledge
• Learn whether a career in data science is right for you
• Gain the skills to pursue a more advanced data science training program

Technical, data analysis or coding skills are not required to take this program. Having experience with data analytics or statistics through work or post-secondary education will be helpful but is not a program requirement.

This program is designed for professionals from diverse backgrounds who want to gain in-demand and highly marketable skills or want to explore data science career options. It can help you cross over to an exciting new career or education path or open up a new range of possibilities in your current field.

You can pay for one course at a time. Begin with the mandatory prerequisite course and then decide whether to continue with additional courses.

All fees are in Canadian dollars, subject to change and to GST (where applicable). For details on forms of payment accepted, please see How to pay.

Find more details on refunds, cancellations and transfers. 

The program has one required course and two to three electives, ranging from seven to nine weeks each. Each course takes approximately 50 hours to complete.

Programming in Python for Data Science is the required course and needs to be completed before starting any electives. The electives can be taken in any order. Minimum two electives are required to receive the program certificate. When registering, please ensure the start date of the elective(s) you choose is after the end date of the Programming in Python for Data Science course.

Please note space in these courses is limited, and registration may close before the course start date, so we encourage you to register as soon as possible.

Required Courses

Elective Courses

The UBC Certificate in Key Capabilities in Data Science is a part-time 100% online program that is facilitator/instructor supported.

You work through course modules on your own time, which are released weekly. Facilitators/instructors host weekly virtual office hours to help with your questions and assignments, and to support you in the course. You also have access to an online forum in which you can post and discuss questions with other students and course facilitators/instructors.

Expected effort

Each course requires approximately 50 hours of study. Expect to spend a minimum of 8 to 10 hours per week on each course if you have coding experience, or 10 to 12 hours per week for beginners.

Technology requirements

To take this program, you need access to:

• an email account
• a computer, laptop or tablet, using Windows or macOS
• the latest version of a web browser (or previous major version release)
• a reliable internet connection
• a video camera and microphone (to access virtual office hours)

Assessment

You are assessed on each course according to UBC assessment guidelines to ensure successful acquisition of required skills and concepts.

To earn your certificate, you must pass the prerequisite course and at least two elective courses. In each course, you must complete the final project and achieve a minimum of 70%.

Obtaining your certificate

When you’ve successfully completed three courses, complete the certificate request form and pay the certificate application fee of $175 to obtain your certificate by mail.

The courses in this program were developed by many of the same instructors as the UBC Master of Data Science program.

• Mike Gelbart, PhD, was part of the team that designed the UBC Master of Data Science curriculum and held the position of Co-Director of the UBC Master of Data Science (Vancouver option).
• Varada Kolhatkar, PhD, is an Associate Professor of teaching in the Department of Computer Science at UBC. She teaches courses in machine learning, natural language processing and artificial intelligence in the undergraduate and the Master of Data Science programs.
• Joel Ostblom, PhD, is a post-doctoral teaching fellow in the Master of Data Science program at UBC.
• Tiffany Timbers, PhD, is Associate Professor of Teaching in the UBC Department of Statistics, and Co-Director for the UBC Master of Data Science (Vancouver option).

Facilitators