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  • Foundations in Rural Data Science

Foundations in Rural Data Science - Certificate

Prepare for one of today’s fastest-growing fields through a blend of analytical, technical and place-based learning.
Program at a Glance
Length
2 years
Credential
Certificate
School
University Arts & Sciences
Delivery Method
On Campus
Campus
Castlegar
Intake Dates
Fall
Contacts
Dylan Sargent
UAS School Chair, Instructor
Phone
1 (888) 953-1133
21318
Contact by email
UAS Program Coordinator
Contact by email
    Overview

    Leveraging data helps communities, organizations and businesses become more competitive and better equipped to adapt to technological and market changes. Without access to context-appropriate data science training, rural communities risk falling behind.

    The Foundations in Rural Data Science Certificate introduces you to one of today’s fastest-growing fields through a blend of analytical, technical and place-based learning. The program builds core skills in data science, computer programming, calculus, statistics and research methods while connecting coursework to real applications in rural and Indigenous community contexts.

    Learn how data is collected, cleaned, analyzed and communicated, and explore how data-driven insights support environmental, community and scientific decision-making. Pathways may lead graduates to continue to an associate of science degree, ladder into related Selkirk College programs (such as Geographic Information Systems) or transfer to a data science degree at another institution.

    Get More Information About Foundations in Rural Data Science

    Program Outcomes

    By the end of the program, graduates will be able to:

    1. Demonstrate best practices across the data science workflow to support decision-making in diverse applied contexts, including those commonly encountered in rural communities.
    2. Apply the mathematical and statistical concepts needed to understand, model, and analyze introductory data science problems, and to continue studies in data-focused disciplines.
    3. Implement foundational computer programming techniques to write, test, and debug code for data science applications.
    4. Examine how the core principles of research design apply to studies in rural and Indigenous settings.  
    5. Using appropriate tools and approaches, create clear reports and visualizations at an introductory level to communicate technical findings for diverse audiences.
    Admission Requirements

    This program is accessible to learners from a wide range of backgrounds. Foundational skills may be demonstrated through prior coursework, professional experience, or a short skills assessment.

    Academic requirements:
     

    • High school graduation or equivalent.
    • English Studies 12, English First Peoples 12 or ENGL 60 with 60% (or equivalent).
    • Pre-Calculus 12 (or equivalent) with a minimum grade of 60%. Applicants who have not completed Pre-Calculus 12 may still be admitted and asked to complete an assessment and upgrade their skills to ensure readiness for university-level mathematics.
    Additional Requirements

    Completion of a questionnaire assessing the student’s computer skills. Basic digital literacy, including file management, online research, and proficiency with common productivity tools, is necessary for success in the program.

    Helpful but not required:
     

    • Experience with spreadsheets, statistics, introductory programming
    • Introductory coding experience (e.g. High school, coding clubs, technology clubs or events
    • Micro-credentials in Python or data literacy

    Application Procedure

    1. Before an applicant's file is considered to be complete, the following must have been received by the Admissions office:
      a) Completed application form.
      b) Official transcripts of high school grades (an interim statement of grades is acceptable if applicant is currently a student).
      c) Official transcripts of all post-secondary education grades.
      d) Computer skills questionnaire, which may be followed up with an interview in some instances. Applicants requiring an
      interview will be contacted. Students may voluntarily withdraw their application or choose to complete preparatory training if,
      following the interview, they determine they do not have the computer skills necessary for success in this program.
    2. Students wishing to enroll in the Foundations in Rural Data Science Program on a part-time basis may do so providing the same entry requirements as full-time students have been met. Part-time students are only accepted if space is available after all full-time students are scheduled and with permission of the School Chair.
    Graduation and Promotion
    • Student academic progress is governed by Policy 8615.
    • Students must meet course pre-requisites with a minimum grade of 60% unless otherwise noted.
    • Foundations in Rural Data Science Certificate is awarded when a student completes at least thirty (30) credits of required and elective courses with a minimum GPA of 2.00.
    Tuition & Fees
    Domestic
    International
    Domestic
    2026/27
    Foundations in Rural Data Science - Certificate, Year 1
    Tuition and Mandatory Fees
    Tuition
    $3,870
    Mandatory Fees
    $475
    Student Union Fees
    $465
    Total
    $4,810
    International
    2026/27
    Foundations in Rural Data Science - Certificate , Year 1
    Tuition and Mandatory Fees
    Tuition
    $14,370
    Mandatory Fees
    $860
    Student Union Fees
    $465
    Total
    $23,495

    All amounts are estimates and are subject to change. Tuition amounts are based on a full-time course load. Please note that many programs have additional costs beyond those listed here. For more information, please visit Tuition & Fees.

    Find Out More

    We look forward to connecting with you! Fill out this form and we'll reach out to you.

     

     

    A member of our recruitment team will be contacting you shortly, keep an eye on your inbox!

    Selkirk College acknowledges the traditional territories of the Sinixt (Lakes), the Syilx (Okanagan), the Ktunaxa and the Secwépemc (Shuswap) Peoples.
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