мÓÆÂÁùºÏ²Ê¹Ù·½ÍøÕ¾

Post Baccalaureate Diploma in Data Analytics and Economics

This diploma in data analytics and economics offers a unique combination of skills and knowledge that individuals can apply to various fields including business, finance, healthcare and government. A strong foundation in economics, statistics and machine learning will allow graduates to make data-informed decisions in their field of practice.

Data science diagnostic test

Share this program

  Email   Print
Commputer screen with coding on it.

Campus

  • Kelowna
View schedule and campus details
Legend:
  • Full program offered
  • Partial program offered

Credential

Diploma

Delivery options

Full-Time

  • International students eligible

Tuition and fees

2024-25: $9,842.92

Program details

This unique two-year post-baccalaureate diploma (60 credit/20 course) is aimed at students with a bachelor's degree in any science, arts, business, nursing, or management program who wish to pursue a career in Data Analytics and Economics. Students will receive thorough training in statistics and data science. Year one of this program sets the mathematical, statistical, and economic foundation for higher-level learning in the economics and data science areas. In second year, students build on and apply these foundational skills to a diverse set of areas. While many of the applications have an economic focus, the mathematical, statistical, and data science concepts learned are universally applicable to a wide range of disciplines.

Campus Start date Schedule
Kelowna Jan. 06, 2025
Kelowna Sep. 03, 2025

Admission requirements

  • Successful completion of a recognized Bachelor Degree in any arts, science, engineering, psychology, business or management program. A post-secondary basic calculus course, or equivalent, is highly recommended.
  • Applicants who have completed post-secondary studies outside of Canada will require a World Education Service evaluation with International Credential Advantage Package of their credentials.
  • A student who has completed a recognized undergraduate degree in a program different than those listed above may be admitted to the program provided they pass the мÓÆÂÁùºÏ²Ê¹Ù·½ÍøÕ¾ College Basic Algebra Proficiency Test with a minimum score of 20/25 AND the Calculus Readiness Test with a minimum score of 16/25.

Program requirements

  • A personal computer is required. See the program for computer specifications.

Program outline

Complete All of the following:
DSCI 300 - Data Wrangling and Visualization
DSCI 310 - Mathematics Computation
STAT 230 - Elementary Applied Statistics
ECON 115 - Principles of Microeconomics
ECON 125 - Principles of Macroeconomics
MATH 314 - Calculus and Linear Algebra with Business Applications
DSCI 400 - Machine Learning I
ECON 201 - Intermediate Microeconomic Analysis
ECON 202 - Intermediate Macroeconomic Analysis
DSCI 420 - Mathematics for Machine Learning
DSCI 401 - Machine Learning II
STAT 310 - Regression Analysis
ECON 251 - Economic Data: Prediction, Analysis and Presentation
STAT 443 - Time Series Analysis and Forecasting
STAT 311 - Modern Statistical Methods
ECON 231 - Introduction to Behavioural Economics
DSCI 491 - Data Science Research Project
Any 200, 300 or 400 level ECON course.
Any 2 electives selected from мÓÆÂÁùºÏ²Ê¹Ù·½ÍøÕ¾ College university transferrable courses.
Notes:
Material from the following courses will be tested on your comprehensive examinations.
• DSCI Comp: DSCI 300, DSCI 310, DSCI 400, DSCI 401
• MATH/STAT Comp: MATH 314, STAT 230, DSCI 420, STAT 310
• ECON Comp: ECON 115, ECON 125, ECON 201, ECON 202

Successful completion of the prescribed and elective courses as listed in the program outline with a minimum graduating grade average of 60%.

Additional information

View the official Calendar details and policies
Learn more about the department
View the Tuition and fees page

Experience

Join an info session or become a student for a day.

Ask

Have your questions answered by an education advisor or future student facilitator. 

Apply

Take the next step and enrol in a program or course at OC.