Programs
The lists specific degree requirements for various programs.
Find out more about:
Please note that since 2021 Math 1111 is not being offered at Mount Allison.
Program Advisors
Math - Dr. Geoffrey Cruttwell - math@mta.ca
Computer Science - Dr. Laurie Ricker- cs@mta.ca
Data Science- Dr. Mark Hamilton- math@mta.ca
GeoComputing
Geocomputing is an exciting new interdisciplinary BA program being offered at Mount Allison. Geocomputing is a joint major BA program that will give students expertise to study and understand spatial dimensions of social and environmental problems. It is an applied program that combines theory and practice of computing and geography, and offers students a new way to look at the world.
Interest in computer science has increased in recent years, with many students hoping to use their computer science skills to enhance another area in which they are interested. Geocomputing offers students a unique way to combine geographical and environmental skills with training in computer science.
Data Science
Program options
Certificate in Data Management (12 credits)
Covers the theory, ethics, and practice of managing and presenting data resources. The certificate will empower students with tools to advance their work in their own discipline, and to progress to graduate or professional practice.
Certificate in Data Analytics (18 credits)
Covers conceptual approaches to analyses of large-scale data, which presents both challenges and opportunities.
Minor in Data Science (24 credits)
Combines both certificates, along with advanced statistics.
New Courses coming Fall 2026!
COMP 1991
This course introduces computing for data science and the fundamentals of programming for data-driven inquiry. Topics include: designing computational solutions for analyzing and manipulating tabular and structured data; developing algorithms and implementing them as modular programs; ensuring program correctness; and the effective use of variables, loops, conditionals, functions, and essential data structures in the context of data science applications.
Additional topics include Boolean logic, numeric and string data, table operations, data filtering and joining, testing, exception handling, and basic error analysis. [Note 1: University preparatory level course in Mathematics is required.] (Format: Lecture 3 hours, Lab 1.5 hours) (Exclusion: MATH 1311, COMP 1611; COMP 1631; COMP 1711; COMP 1731; any COMP course at the 2000 level or higher)
DATA 1991
This course surveys foundational ideas in data exploration, visualization, and analysis. Students are introduced to elementary probability, descriptive statistics, and data visualization techniques used in data science.
Building on the fundamental computational concepts introduced in COMP 1991, the course also provides an overview of introductory methods for analysis and prediction, including linear and logistic regression and random forest models, while emphasizing interpretation of uncertainty and results through concepts such as confidence intervals and p-values.
IMPORTANT NOTE: Do not register for both Comp 1631 and Comp 1991!
Pursuing Honours degree in Math or Comp Sci
If you are intended to do an honours thesis, please let the department know by filling out this departmental form
Application form- Honours thesis
Once confirmed, you are required to fill out the official Declaration of Honours via the Registrar's office here:
/current-students/academics-current-students/records-documents-and-forms/declaration-pursue-honours
Sequence of upper-year courses
The following is the intended sequence of upper year course offerings for the next two years. Note that many factors could change this plan slightly.
Mathematics
Fall 2026
Math 3111 - Real Analysis
Math 3221 - Advanced Linear Algebra
Math 3411 - Numerical Analysis
Winter 2027
Math 3131 - Differential Equations II
Math 3141 - Vector Calculus
Math 3231 - Number Theory
Math 3311 - Probability and Statistics I
2027-2028 Tentative
Math 3111 - Real Analysis
Math 3161 - Complex Variables with Applications
Math 3211 - Modern Algebra I
Math 3251 - Graph Theory
Math/Econ 3301 - Game Theory
Math 3991 - Optimization
Math 4111 - Topology
Math 4221 - Modern Algebra II
Math/Comp 4651 – Cryptography
Math 3xxx Applied math course TBD
Computer science
Fall 2026
Comp/Phys 3361 - Digital Signal Processing &
Electronic
Comp 3611 - Algorithm Analysis
Comp 3651 - Artificial Intelligence
Comp 3831 - Computer Graphics
Comp 4721 - Software Design
Winter 2027
Comp 3851 - Computers and Society
Comp 3971 - Computer Organization and
Architecture
Comp/Math 4631 - Theory of Computation
2027-2028 Tentative
Comp 3611 - Algorithm Analysis
Comp 3621 - Advanced Data Structures
Comp 3711 - Principles of Programming Languages
Comp 3811 - Database Systems
Comp 3911 - Operating Systems
Comp/Math 4651 - Cryptography
Comp 4721 - Software Design
Comp 4911 - Computer Networks
Data
2026-2027
Data 3001 - Data Visualization & Communication
Data 3101 - Data Acquisition & Organization
Data 4001 - Advanced Methods in Data Science
2027 -2028
Data 3001 - Data Visualization & Communication
Data 3101 - Data Acquisition & Organization
Registering for calculus
2021 onward
- MATH 1151 (Applied Calculus) will be offered
- MATH 1111 (Calculus I) will not be offered
Students may use MATH 1151 as a prerequisite for MATH 1121 (Calculus II) any MtA program that currently requires MATH 1111 has agreed to accept MATH 1151 in its place.
Math Assessment Test
Students registering in MATH 1151 are required to pass a Math Assessment Test. Click for further Information regarding the test and some FAQs.
Generally, students who struggle with the Math Assessment Test, also struggle with calculus. Students who do not pass the Math Assessment Test can take MATH 1011 to help prepare them for success in calculus.
If you have any questions, please contact the mathematics program advisor at math@mta .
Challenge for Credit
°®¶¹´«Ã½app may recognize prior learning for certain courses through challenge for credit when students have obtained a proficiency or intellectual skills in the subject matter through training or experience rather than through high school, college, or previous university instruction.
Only students who have been admitted to, or are currently registered in, a degree program at °®¶¹´«Ã½app may challenge for credit.
Please note:
- A student who wishes to challenge a course must complete the Challenge for Credit form (link here) at least one month before the beginning of the fall or winter term.
- See for regulations, procedures, and eligibility.
- There is a fee of $375 to challenge for credit.
- If approved, the student will be contacted by the registrar's office for arrangements for examination.
Further Important Information
The Department of Mathematics and Computer Science currently offers in-person Challenge for Credit in:
Math 1111 Calculus I
This course introduces differential calculus. Topics include derivatives of algebraic, trigonometric, and exponential functions and applications such as curve sketching, related rates, and optimization problems. [Note 1: This course has a Challenge for Credit option; see Calendar Section 3.11] (Format: Lecture 3 Hours, Laboratory 1.5 Hours)(Distribution: Natural Science-a) (Exclusion: MATH 1151; any version of MATH 1111 previously offered with a different title)
If successfully challenged, a student will receive credit for MATH 1111, without having to take the course. You will write a comprehensive examination what covers the entire content of MATH 1111 (Calculus I), held before or during the first week of the fall or winter semester on campus. You must achieve a grade of C- or higher to succeed in the challenge.
Below is a sample exam:
Math 1111 currently uses the textbook “Essential Calculus – Early Transcendentals†(2nd Ed) by James Stewart and covers material from Chapters 1-4 inclusive (excluding Sections 3.6 and 4.6).