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  • Foundations in Rural Data Science

Foundations in Rural Data Science

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 terms
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

    Data is shaping the future of work and the Foundations in Rural Data Science Certificate at Selkirk College gives you the skills to be part of it. This beginner-friendly program teaches you how to analyze, interpret, and communicate data while applying those skills to real challenges in rural communities.

    Apply Now!Get More Information About Foundations in Rural Data Science

    Build In-Demand Data Skills

    Data science is one of the fastest-growing fields in Canada and globally. Employers across industries are looking for people who can turn data into insights. In this program, you’ll learn:

    •    Data analysis and visualization
    •    Programming fundamentals
    •    Statistics and problem-solving
    •    How to communicate data insights clearly

    These are transferable, future-proof skills that apply to careers in business, healthcare, environmental science, and more.

    Start Your Data Science Journey: No Experience Required

    This certificate is a true entry point into data science, with step-by-step learning that builds your confidence and technical ability from the ground up. You don’t need advanced math or coding experience, just curiosity and a willingness to learn. You’ll gain:

    •    Experience working with real datasets
    •    Exposure to applied research projects
    •    Opportunities to connect with regional organizations

    Graduates can 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.

    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

    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.
    Courses
    Term 1
    Required courses

    CPSC100 - Introduction To Programming I

    CPSC 100 Introduction to Computer Programming I is an introductory object-oriented (OO) programming course with emphasis on basic programming constructs, algorithms, program design, and good programming practices. This course will introduce a high-level language to illustrate programming basics. Students will develop and test small OO programs which loop, make decisions, access arrays, define classes, instantiate objects, and invoke methods.

    Prerequisites
    Foundations of Math 12 or Pre-calculus 12 or MATH 60 with a minimum grade of 60%
    Credits
    3.00

    MATH100 - Calculus I

    MATH 100 Calculus I is a course designed to provide students with the background in calculus needed for further studies. This course includes a review of functions and graphs; limits; the derivative of algebraic, trigonometric, exponential and logarithmic functions; applications of the derivative including related rates, maxima, minima, velocity and acceleration; the definite integral; an introduction to elementary differential equations; and applications of integration including velocity, acceleration, areas, and growth and decay problems.

    Prerequisites
    Pre-Calculus 12 or MATH 60 with a minimum grade of 67%
    Credits
    3.00

    ENGL110 - College Composition

    ENGL 110 introduces students to the world of scholarly writing -- reading it, thinking about it, and producing it as academic researchers. Students will explore how professional and/or academic writers across disciplines communicate to a variety of audiences. Students will practice active reading, writing and critical thinking skills by conducting scholarly research on a topic. This course aims to equip students with the skills and knowledge they need to write effectively within academic contexts.

    Prerequisites
    English Studies 12 or English First Peoples 12 or ENGL 60 with a minimum grade of 60%
    Credits
    3.00

    RDS100 - Introduction to Data Science

    RDS 100 Introduction to Data Science introduces the foundations of data science through programming and exploratory data analysis. Students will develop essential coding skills, use version control, apply basic data cleaning and wrangling techniques to prepare datasets for analysis, and create effective visualizations. Core topics include an introduction to statistical inference, regression, classification, and clustering. Emphasis is placed on reproducible workflows in notebooks, enabling students to build confidence in coding while analyzing real-world datasets.

    Prerequisites
    Minimum grade of 60% in Pre-Calculus 12 or equivalent
    Credits
    3.5

    ELECTIVE - Course
    Credits
    3.00


    Elective Courses

    Students should select elective courses based on their anticipated pathways to further education; please meet with a Selkirk College counsellor or the school chair to discuss course options.

    Recommended electives include:

    • For those continuing as Associate of Science students in their second year, see the Graduation and Promotion requirements to ensure chosen electives fit with that program.
    • For those transferring to data science or related programs at other institutions, check their program requirements.

    See the UAS Courses by discipline page for course selections.


    Term 2
    Required courses

    MATH101 - Calculus II

    MATH 101 Calculus II is a sequel to Math 100 for students who wish to major in science, math or engineering and includes the definite integral, applications of the definite integral to volume, arc length and surface area of revolution; inverse trig functions; techniques of integration; improper integrals; parametric equations and polar coordinates; linear first order differential equations; and an introduction to infinite series; convergence and power series; Taylor Polynomials.

    Prerequisites
    MATH 100 with a minimum grade of 60%
    Credits
    3.00

    CPSC101 - Introduction To Programming II

    CPSC 101 Introduction to Computer Programming II course is a continuation of CPSC 100 with emphasis on more advanced programming techniques and design, development and test of large applications. Students will write programs which make use of library functions to display graphical user interfaces, manage collections of data, access files and databases, and interact with other programs.

    Prerequisites
    CPSC 100 with a minimum grade of 60%
    Credits
    3.00

    RDS101 - Foundations in Rural Research

    RDS 101 Foundations in Rural Research is a highly participatory course that examines how rural contexts influence research and data. Through discussions, readings, reflections, and guest lectures, the course emphasizes ethical and place-based considerations, including Indigenous data sovereignty, data equity, the digital divide, and rural data gaps. Students will explore rural-appropriate research methods and the types of professional experiences and careers that involve research in rural settings. Students will leave the course with the ability to analyze rural research critically.

    Credits
    3

    ELECTIVE - Course
    Credits
    3.00

    ELECTIVE - Course
    Credits
    3.00

    Elective Courses

    Students should select elective courses based on their anticipated pathways to further education; please meet with a Selkirk College counsellor or the school chair to discuss course options.

    Recommended electives include:

    • For those continuing as Associate of Science students in their second year, see the Graduation and Promotion requirements to ensure chosen electives fit with that program.
    • For those transferring to data science or related programs at other institutions, check their program requirements.

    See the UAS Courses by discipline page for course selections.

    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
    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!

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