The Vancouver Summer Program with UBC Science provides students with the opportunity to study at a top international research university and experience local Vancouver culture.

What you might expect/course format

Courses with UBC Science include in-class and lab portions taught by UBC faculty members, graduate students, and guest lecturers. Courses also include short field trips and other engaging learning opportunities. Students can expect team-based learning activities and assignments.

July 2024 Course Packages

Statistical Literacy and Reasoning in Data Science

In this course, students will develop statistical literacy and reasoning, building their capacity for deep understanding of data and making data-driven decisions. Through carefully designed lectures, practical exercises, assignments and a group project, participants will acquire a fundamental understanding of study design and data collection. This will empower the students to systematically organize their own analysis projects and collect representative and trustworthy data. The course learning objectives are: i). building basic data literacy and reasoning, ii). improving students’ capacity to formulate data-driven problems, iii). designing and properly applying appropriate statistical methodologies such as data visualizations, t-test, ANOVA, correlation and linear regression, iv). empowering them to understand data trends, anomalies, and patterns, v). interpreting results, and v). developing written and oral communication skills to present data-driven insights.

Data Science Tools and Advanced Modeling Techniques

In this course, students will gain practical skills to implement the best data science practices. Students will master data manipulation and graphical skills, understand advanced statistical models for complex datasets, and will get familiar with the field of neural networks and deep learning. Students will master automatic version control with Git and acquire strong cooperation skills by immersing themselves in the world of collaborative, reproducible research. Through applying their command of statistical reasoning, analysis, and visualization, students will be empowered to generate powerful, data-driven storytelling in the course’s final presentation. The main learning objectives of this course are: i). master data manipulation and visualization, ii). develop reproducible data workflows, iii). use automatic version control with git and GitLab, iv). communicate the important steps of data analysis workflows, and v). extract subtle insights from complex data structures.

Prerequisite: No prerequisites

Additional information: Laptop required. Software setup required prior to first class. Setup instructions will be provided.

For more information

For VSP Statistics and Data Science-specific questions, email Biljana Stojkova at

Student testimonials

“My favorite part of VSP was the connections I made with people, both inside and outside of the program. I also loved the laboratories.” VSP taught me many things, both knowledge and character development. The lectures were very knowledgeable especially when Hadi Sir used to teach us.

…He would make us think in ways we couldn’t even imagine. Our perspective over certain things changed a lot.”

– VSP Science Student, 2019