Math 2121 (Fall 2018)
Overview
Welcome to the homepage for Math 2121: Linear Algebra!
- Send questions for the instructor to emarberg@ust.hk or matom@ust.hk.
- Send questions about grades to your TA.
Check out the syllabus here.
Lectures
- L1: Mondays 1:30-2:50PM, Fridays 9:00-10:20AM, Lecture Theater C
- L2: Mondays 3:00-4:20PM, Fridays 10:30-11:50AM, Lecture Theater C
- L3: Mondays, Wednesdays 12:00-1:20PM, Room 4619, Lift 31-32
Office hours
- Eric: Room 3492, Lift 25-26.
- Jian-Shu: Room 3458, Lift 25-26.
Drop by anytime, or send an email to make an appointment.
Textbook
Linear Algebra and its Applications, 5th edition, by D. Lay, S. Lay, and J. McDonald
Other resources
Linear Algebra Done Right by Axler is a great supplementary textbook.
Khan academy has many good instructional videos on linear algebra and other topics.
HKUST professor Jeffrey Chasnov has launched a Coursera course called Matrix Algebra for Engineers which covers some of the same material as our class. The course can be accessed for free online and has many helpful videos, notes, and exercises.
Some students have recommended this YouTube channel dedicated to linear algebra topics.
Grading
Grades will be computed as follows:
- 10%: homework assignments, weighted equally
- 30%: midterm examination
- 60%: final examination
Midterm examination
- The midterm will be on 19 October from 10:00AM to Noon, replacing Friday's lectures
- Email your instructor right away if you have a conflict.
- Midterm location:
- Even student IDs: Lecture Theater B
- Odd student IDs: Lecture Theater C
- Information on what to study:
- Midterm solutions
Final examination
- Logistics for the final examination:
- Date: 14 December
- Time: 8:30 AM to 11:30 AM
- Location: S H Ho Sports Hall
- There will be no alternate exam times.
- Information on what to study:
Schedule
The following is a tentative course outline:
- Week 1: Linear systems, row reduction to echelon form (reading: Sections 1.1-1.2)
- Week 2: Vectors, matrix equations, linear independence (reading: Sections 1.3-1.5, 1.7)
- Week 3: Linear independence, linear transformations (reading: Sections 1.7-1.9)
- Week 4: Matrix multiplication, the inverse of a matrix (reading: Sections 2.1-2.3)
- Week 5: Subspaces, null and column space (reading: Sections 2.4, 2.8)
- Week 6: Dimension, rank, determinants (reading: Sections 2.9, 3.1-3.2)
- Week 7: Determinants, midterm (reading: Sections 3.1-3.2)
- Week 8: Vector spaces, eigenvectors, and eigenvalues (reading: Sections 4.1-4.6, 5.1)
- Week 9: Similarity and diagonalisable matrices (reading: Sections 5.2-5.4)
- Week 10: Complex eigenvalues, properties of eigenvalues (reading: Sections 5.5, 6.1)
- Week 11: Inner products, orthogonality, and projections (reading: Sections 6.1-6.3)
- Week 12: Gram-Schmidt process, least-squares problems (reading: Sections 6.4-6.6)
- Week 13: Symmetric matrices, SVDs (reading: Sections 7.1, 7.4)
Lecture notes
- Week 1:
- Week 2:
- Lecture 3: Vectors in Euclidean space
- Lecture 4: Matrix-vector products, linear independence
- Week 3:
- (No lecture on Monday due to cancellation)
- Lecture 5: Linear independence, linear transformations, one-to-one and onto functions
- Week 4:
- Lecture 6: Matrix operations, matrix multiplication
- Lecture 7: Invertible functions and matrices
- Week 5:
- (No lecture on Monday due to public holiday)
- Lecture 8: Subspaces, null and column space of a matrix
- Week 6:
- Week 7:
- Lecture 11: Properties of the determinant
- (Midterm exam on Friday, no lectures on Wednesday/Friday)
- Week 8:
- Week 9:
- Lecture 14: Similar and diagonalizable matrices
- Lecture 15: Fibonacci numbers and repeated eigenvalues
- Week 10:
- Week 11:
- Lecture 18: Orthogonal vectors and orthogonal projections
- Lecture 19: More on projections, Gram-Schmidt process
- Week 12:
- Week 13:
Assignments
Homework will be submitted online using WeBWorK.
Assignments will be due at midnight each Tuesday.
- The first homework assignment will be due on 11 September.
- No homework due on 23 October.
- The last homework assignment will be due on 29 November.