Introduction
information
Theses are my notes on MATH 2121: Linear Algebra
Course information
- Course code: MATH 2121
- Course title: Linear Algebra
- Semester: 24/25 Fall
- Credit: 4
- Grade: A-F
- TMI
- Prerequisite: A passing grade in AL Pure Mathematics / AL Applied Mathematics; OR MATH 1014 OR MATH 1020 OR MATH 1024
- Exclusion: MATH 2111, MATH 2131, MATH 2350
Description
This will be a first course in linear algebra, from an applied perspective. The main topics covered will include solving linear systems of equations, vector spaces, matrices, linear mappings and matrix forms, inner products, orthogonality, eigenvalues and eigenvectors, and symmetric matrices. No prior knowledge of matrix algebra is assumed.
My section
- Section: L1 / T1D
- Time:
- Lecture: TuTh 03:00PM - 04:20PM
- Tutorial: We 06:00PM - 06:50PM
- Mid-Term: Oct 17 08:00PM - 10:00PM
- Venue:
- Lecture: G010, CYT Bldg
- Tutorial: Rm 1104, Acad Concourse
- Instructor: MARBERG, Eric Paul
- Email: [email protected]
- Room: Rm 3492, Lift 25-26
- Teaching Assistants:
- WANG, Kaibo ([email protected])
Grading scheme
| Assessment Task | Percentage |
|---|---|
| Online HW | 5% |
| Offline HW | 5% |
| Mid-Term | 30% |
| Final Exam | 60% |
- lowest online & offline HW scores: will be dropped
- Online HW: due Mon midnight (from 9 Sep)
- Offline HW: choose 4 problems & solve; due Wed midnight (from 11 Sep)
Extra credit
If you submit correct solutions to extra practice problems, then you can earn extra credit. You can earn up to 5% extra credit for your course grade in this way over the whole semester. See the instructions for the offline homework assignments on the course website.
Tentative Schedule
| Week | Topic | reading |
|---|---|---|
| 1 | Linear systems, row reduction to echelon form | 1.1-1.2 |
| 2 | Vectors, matrix equations, linear independence | 1.3-1.5, 1.7 |
| 3 | Linear independence, linear transformations | 1.7-1.9 |
| 4 | Matrix multiplication, the inverse of a matrix | 2.1-2.3 |
| 5 | Subspaces, bases, dimension | 2.4, 2.8-2.9 |
| 6 | Determinants | 3.1-3.2 |
| 7 | Vector spaces, midterm | 4.1-4.6 |
| 8 | Eigenvectors, and eigenvalues | 5.1 |
| 9 | Similarity and diagonalisable matrices | 5.2-5.4 |
| 10 | Complex eigenvalues, properties of eigenvalues | 5.5, 6.1 |
| 11 | Inner products, orthogonality, and projections | 6.1-6.3 |
| 12 | Gram-Schmidt process, least-squares problems | 6.4-6.6 |
| 13 | Symmetric matrices, SVDs | 7.1, 7.4 |
Required texts
- Linear Algebra and its Applications, by D. Lay, etc. (6th edition)
Optional resources
- N/A