Data Science

Wilfrid Laurier University · Waterloo

Mathematics and Statistics: blue ink subject illustration

4 years
Duration (years)
4 years
Laurier Waterloo · Data Science BSc
Co-op option
Work experience
Co-op option
Laurier Data Science programme and requirements
~Mid 70s
Entering average
Published approximate guidance: Mid 70s. Fall 2027. Ontario high school applicants, OUAC UDS, Waterloo campus
Laurier Data Science programme and requirements

Deadlines

November 2026

Mon	Tue	Wed	Thu	Fri	Sat	Sun
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2	3	4	5	6	7	8
9	10	11	12	13	14	15
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23	24	25	26	27	28	29
30

Next deadlineThursday, November 19, 2026

OUAC. Ontario high schools report midterm/final 4U/M grades
2027 entry
School deadline, not a student task. Universities receive these grades by November 26. Verbatim: "Deadline for the OUAC to receive all midterm or final grades available for 4U/M courses from Ontario high schools. Schools may report in-progress grades for full-year courses as soon as they are available." Universities receive these by the target date of November 26, 2026. This is a deadline on the high school, not on the student, but it governs which grades a university sees in the first round.
Official deadline

Other deadline details

No single OUAC deadline, deadlines are set by each university and sometimes by programOUAC Undergraduate application, applicants who are not Ontario high school students (Group B)2026 entry

No single OUAC deadline, deadlines are set by each university and sometimes by program
No single OUAC deadline
University, program, transcript, portfolio, interview, and audition dates still apply

Full source wording

Verbatim: "There is no specific Undergraduate application deadline if you are a Group B applicant. Deadlines vary at each university and sometimes depend on the program. Visit the university websites or contact the universities directly for their deadlines. If you are interested in a program but the deadline has passed, you may contact the university's admission office for help. Be aware of university-specific deadlines for submitting transcripts and portfolios, if required, and for arranging interviews and auditions. You must ensure the OUAC has enough time to process your choices before the universities' program deadlines." OUAC defines Group B as anyone who does not meet the Group A criteria, e.g. not currently taking an Ontario high school course, a Canadian outside Ontario, an international applicant, a postsecondary transfer student, or a mature applicant.

SourceChecked Aug 14, 2026

Requirements

Admission requirements

High-school prerequisites

ENG4UEnglish70% min.
MHF4UAdvanced Functions80% min.
MCV4UCalculus and Vectors80% min.

All prerequisite grades count in the admission average.

Application steps

Step 1Check the admission requirements
- Check the published entry route for your applicant category.
Laurier Data Science programme and requirementsLaurier Data Science programme and requirements
Step 2Apply through OUAC
- Create your application and select this program.
OUACOUAC
Step 3Academic transcripts for your applicant group
- Current Ontario high school grades and OSSD status arrive automatically through OUAC. Other applicants provide the portal's requested records from attended schools and postsecondary institutions. Unofficial records go through the portal, not email; final official records come directly from the issuer after accepting an offer.
Laurier required application documentsLaurier required application documents
Step 4Notarized English translations, if applicable
- Records written outside English require original-language copies and a notarized literal English translation.
Laurier document translation requirementsLaurier document translation requirements
Step 5English test results if fewer than three years of English study
- Submit satisfactory accepted results if you have not studied full-time in English for at least three years. Applicants asked for proof may request exemption when they meet that published schooling condition.
Laurier English-proof document conditionsLaurier English-proof document conditions
Step 6Apply through OUAC using UDS.
- Complete this item using the university’s applicant instructions.
Laurier Data Science programme and requirementsLaurier Data Science programme and requirements

Degree requirements

Required courses and electives

The Honours BSc requires 20.0 credits: 12.0 core, 2.5 concentration and 5.5 elective credits.

References

Grades and academic standing

Graduation requires at least a 5.0 overall GPA, at least 5.0 in MA/ST/DATA courses, and at least 5.0 in Computer Science courses. Progression into years after Year 2 requires at least 4.0 overall.

References

Work and practical requirements

The co-op grid places the regular Year 3 fall academic block in Year 2 spring and the regular Year 4 winter block in Year 4 spring. Its work terms are Year 3 fall, Year 3 spring and Year 4 winter.

References

Program facts

Entering average~Mid 70s

Ontario high school applicants, OUAC UDS, Waterloo campus

Co-opCo-op option

Check work experience options

Majors & specializations

Big Data Concentration

BSc

Required courses cover big data programming, computer networks and artificial intelligence.

Published requirements

Courses

First-year courses shown by the named degree or option. Confirm requirements in your entry-year calendar. The 2026–27 regular and co-op Data Science schedules use different academic terms in later years.

Year 1 fall7 listed

BU111Understanding the Business Environment0.5 credits
Examine competitive, political, economic, social and technological influences on business decisions through cases and business proposals.
Choose BU111 or ENTR100.
Laurier 2026/27 selected programme requirements
ENTR100Introduction to Business Principles for Entrepreneurs0.5 credits
Laurier calendar · ENTR100
CP104Introduction to Programming0.5 credits
Solve problems through structured programming in a high-level language.
Laurier 2026/27 selected programme requirements
DATA100Introduction to Data Analytics0.5 credits
Use R to prepare, visualise and model data and to apply descriptive statistics.
Laurier calendar · Data Science courses
MA123Introductory Linear Algebra with Applications0.5 credits
Use linear algebra and computational software in finance and science applications.
Choose MA123 or MA122.
Laurier 2026/27 selected programme requirements
MA122Introductory Linear Algebra0.5 credits
Study vectors, matrices, linear systems and eigenvalues.
Laurier 2026/27 selected programme requirements
MA102Introduction to Functions and Differential Calculus0.5 credits
Study functions, equations, limits and introductory differential calculus.
May be needed before MA103 based on the calculus evaluation.
Laurier 2026/27 selected programme requirements

Year 1 winter4 listed

The calendar includes two 0.5-credit elective slots and lists EC140 as an option in one.

CP164Data Structures I0.5 credits
Laurier Waterloo Faculty of Science first-year course registration guide
MA120Foundations and Applications of Mathematics0.5 credits
Develop mathematical reasoning and use advanced mathematical ideas to investigate real-world examples.
Choose MA120 or MA121.
Laurier 2026–27 Academic Calendar · MA120
MA121Introduction to Mathematical Proofs0.5 credits
Learn mathematical writing and proof methods, including contradiction, induction, and counterexamples.
Laurier 2026–27 Academic Calendar · MA121
MA103Calculus I0.5 credits
Study limits, differentiation, integration and series in single-variable calculus.
Laurier 2026/27 selected programme requirements

Regular Year 2 · Fall4 listed

Add 0.5 elective credit.

CP213Introduction to Object-Oriented Programming0.5 credits
Learn object-oriented Java programming, including classes, inheritance, and event-driven and concurrent code.
Laurier 2026–27 Academic Calendar · CP213
CP363Database I0.5 credits
Study database design, data models, query languages, concurrency, recovery, and security.
Laurier 2026–27 Academic Calendar · CP363
MA200Advanced Calculus0.5 credits
Study infinite series, Taylor expansions, partial derivatives, gradients, and optimization with several variables.
Laurier 2026–27 Academic Calendar · MA200
ST259Probability I0.5 credits
Study conditional probability, independence, random variables, expectation, variance, and covariance.
Laurier 2026–27 Academic Calendar · ST259

Regular Year 2 · Winter4 listed

Add 0.5 elective credit.

CP264Data Structures II0.5 credits
CP321Data Visualisation0.5 credits
Learn to visualize and interpret large datasets for evidence-based analysis.
Laurier 2026–27 Academic Calendar · CP321
MA238Discrete Mathematics0.5 credits
Study graphs, trees, relations, counting methods, recurrence relations, and inclusion-exclusion.
Laurier 2026–27 Academic Calendar · MA238
ST260Introduction to Statistics0.5 credits
Use exploratory data analysis, probability models, estimation, and hypothesis tests to draw statistical conclusions.
Laurier 2026–27 Academic Calendar · ST260

Regular Year 3 · Fall3 listed

Add 0.5 senior CP/DATA/MA/ST and 0.5 degree elective credit.

CP312Algorithm Design and Analysis I0.5 credits
Analyze algorithm performance and compare strategies including greedy search, divide and conquer, and backtracking.
Laurier 2026–27 Academic Calendar · CP312
CP317Software Engineering0.5 credits
Study how software is planned, designed, implemented, tested, and managed using traditional and object-oriented methods.
Laurier 2026–27 Academic Calendar · CP317
ST362Regression Analysis0.5 credits
Study regression models, statistical tests, diagnostics, and approaches to selecting variables.
Laurier 2026–27 Academic Calendar · ST362

Regular Year 3 · Winter6 listed

Choose one of DATA200, CP422 and BU425. Add 0.5 degree elective credit.

CP322Machine Learning0.5 credits
Study predictive machine learning methods, including regression, classification, and neural networks.
Laurier 2026–27 Academic Calendar · CP322
CP421Data Mining0.5 credits
Study information retrieval and data mining through practical methods such as document indexing and relevance ranking.
Laurier 2026–27 Academic Calendar · CP421
ST494Statistical Learning0.5 credits
Compare methods for supervised learning, including classification and regression, and unsupervised methods such as clustering.
Laurier 2026–27 Academic Calendar · ST494
DATA200Data Analytics0.5 credits
Work through the data science process from formulating questions and cleaning data to inference, prediction, and decisions.
Laurier 2026–27 Academic Calendar · DATA200
CP422Programming for Big Data0.5 credits
Study data storage and analysis at scale using distributed processing, statistics, and machine learning.
Laurier 2026–27 Academic Calendar · CP422
BU425Business Analytics0.5 credits
Use statistical and machine learning techniques to analyze business data and guide decisions.
Laurier 2026–27 Academic Calendar · BU425

Regular Year 4 · Fall2 listed

Choose MA371 or ST361. Add 1.0 senior CP/DATA/MA/ST and 1.0 degree elective credit.

MA371Computational Methods for Data Analysis0.5 credits
Use R or MATLAB to study computational techniques for data analysis, including numerical linear algebra.
Laurier 2026–27 Academic Calendar · MA371
ST361Mathematical Statistics0.5 credits
Study parametric inference, likelihood, estimation, and hypothesis testing.
Laurier 2026–27 Academic Calendar · ST361

Regular Year 4 · Winter1 listed

Add 1.0 senior CP/DATA/MA/ST and 1.0 degree elective credit.

CP373Ethics and Professional Practice in Computer Science0.5 credits
Examine computing ethics, including privacy, safety, intellectual property, and the effects of technology on work and society.
Laurier 2026–27 Academic Calendar · CP373

Elective choices

The calendar permits up to 7.0 credits at the 100 level.
Choose 2.5 senior CP/MA/ST/DATA credits for concentration requirements, including at least 2.0 at the 300 or 400 level. CP214 cannot meet the senior CP requirement.
At least 0.5 elective credit must be from outside the Faculty of Science. UU201 cannot be used as an elective.

Study locations