MAT223: Linear Algebra I (Fall 2026)


Course Links


Important Dates and Announcements

  • Tutorials will begin in Week 3 of the semester, on September 21st.

  • Webwork is due every Friday at 5pm, and can be accessed via our Quercus page.

  • Chapter Activity Packets are assigned in lecture each week, and must be submitted to Gradescope by 5pm the following Monday.

Course Calendar

Week Material Chapter Activity Packet Tutorial Activity
1 (Sep 7 - 11) Chapter 1: Systems of Linear Equations CAP1 (s): due Sep 14 No tutorial this week
2 (Sep 14 - 18) Chapter 2: Vectors in Euclidean Space CAP2: due Sep 21 No tutorial this week
3 (Sep 21 - 25) Chapter 3: Vector Subspaces of R^n CAP3: due Sep 28 Exam Prep 1
4 (Sep 28 - Oct 2) Chapter 4: Linear Transformations CAP4: due Oct 5 Proofs and Problem Solving 1
5 (Oct 5 - 9) Chapter 5: Fundamental Subspaces CAP5: due Oct 13 Exam Prep 2
6 (Oct 12 - 16) Chapter 6: Matrix Algebra CAP6: due Oct 19 Thanksgiving Holiday on Oct 12 (no tutorial this week)
7 (Oct 19 - 23) Chapter 7: Determinants CAP7: due Nov 2 Exam Prep 3

Reading Week: Oct 26 - 30 (no lectures or tutorials)


Week Material Chapter Activity Packet Tutorial Activity
8 (Nov 2 - 6) Chapter 8: Coordinate Systems and Change of Basis CAP8: due Nov 9
Proofs and Problem Solving 2
9 (Nov 9 - 13) Chapter 8 continued

Chapter 9: Eigenvalues and Eigenvectors
CAP9: due Nov 16 Exam Prep 4
10 (Nov 16 - 20) Chapter 10: Similarity and Diagonalization CAP10: due Nov 23 Proofs and Problem Solving 3
11 (Nov 23 - 27) Chapter 11: Orthogonality CAP11: due Nov 30 Exam Prep 5
12 (Nov 30 - Dec 4) Chapter 12: Singular Value Decomposition CAP12: due Dec 7 Proofs and Problem Solving 4
13 (Dec 7) Makeup tutorial on Monday (no lectures) Exam Prep 6
Finals exams
(Dec 10 - 22)
Final Exam Date TBD


Office Hour Calendar

link to calendar



Frequently Asked Questions

We'll be using research-based teaching and learning methods in this course, including inquiry-based learning. Many of the course activities will aim to guide you through the process of discovering content, which is known to lead to deeper understanding and retention of course material than the traditional lecture-based model.

You are welcome to work on your own during lecture activities if you prefer. We suggest you at least try working with your classmates for the first couple weeks to see if you find the discussion helpful. You will be expected to collaborate with your groups during tutorial activities.

Makeup work or extensions on assignments will generally not be allowed in this course. There is flexibility built into the course to account for any absences. Please see the "Assessment and Grading" section on our course syllabus for details. To catchup on missed lectures read the lecture notes and/or watch the associated lecture recordings available on our Quercus page.

You are welcome and encouraged to attend any of the office hours posted on the office hour calendar above, even instructor office hours that you are not enrolled with. You may also consider posting a question on our course Piazza (available on our Quercus page), or using the resources at the Math Learning Centre.

We ask that you first carefully read the course syllabus before sending any emails. If you have a question about your grade in the course, please reach out to your course instructor. All other logistics related questions that cannot be answered by carefully reviewing the course syllabus should email the administrative inbox listed on the course syllabus.