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Linear Algebra and Applications

MAT2041, Fall 2023

Course Information

Table of contents

  1. MAT2041, Fall 2023
    1. Course Materials
    2. Online communication channels
    3. Logistics
      1. Session L1
      2. Session L2&L3
      3. Office hours
      4. Tutorial
    4. Course Description
    5. Learning Outcomes
    6. Grading Scheme
    7. Policy for assignments and exams
    8. Regrade requests
    9. Suggestions
    10. General Course Policies:
    11. Attendance requirement

Course Materials

The course materials can be found in HERE

Online communication channels

  • This website: a collection of links, announcements, course material, homeworks, etc.
  • Piazza: sign up at HERE, for discussion
  • Wechat group: daily discussion and announcements, etc.
  • Blackboard: submit homeworks. Only occassionally used for posting announcements.

Logistics

Session L1

Time: 09/04/2022-12/16/2022 Exam Week: (12/17-12/24)

Instructor: Hongyuan Zha zhahy@cuhk.edu.cn

Course Schedule: Tue & Thu 8:30AM - 9:50AM

Venue: Teaching B Bldg 104

Session L2&L3

Instructor: Ruoyu Sun sunruoyu@cuhk.edu.cn

Course Schedule:

L2: Tue & Thu 10:30AM-11:50AM

L3: Tue & Thu 1:30PM-2:50PM

Venue:

L2: Zhixin Bldg 110

L3: Zhixin Bldg 111

Textbook: “Introduction to Linear Algebra”, Gilbert Strang, 6th Edition, Wellesley-Cambridge Press. (The 6th edition is recommended, but the 5th is also okay)

Secondary reference book “Introduction to Applied Linear Algebra”, Steven Boyd, Lieven Vandenberghe. (some material from this book)

Office hours

See HERE

Tutorial

See HERE

Course Description

This course is intended to be an introduction to and survey of deterministic optimization models with applications to systems found in operations research. The student should complete this course with the ability to identify problems that can be addressed using operations research models, as well as the ability to use such models to solve problems.

Learning Outcomes

Following the completion of this course, students should be able to

  1. Understand of the concepts of linear algebra.
  2. Become proficient in the basic matrix calculations, such as addition, multiplication, inverse, and determinants.
  3. Get knowledge of matrix decompositions, such as LU, QR and SVD.
  4. Understand the theory of linear algebra, such as linear independence, vector spaces, orthogonality, and eigen-theory.
  5. Applying linear algebra tools to data science.

Grading Scheme

  • Assignments and Quizzes: 35%
  • Midterm exam: 30%
  • Final exam: 35%

(There maybe some in-class quizzes, contributing a random portion from 0% to 5% to the final score.)

Policy for assignments and exams

  • Problem sets will be assigned approximately biweekly. Homeworks should be submitted as a single PDF file to Blackboard by 10pm Beijing Time on the due date, or earlier. More details and instructions about the homework submission will be provided in the assignments.
  • Late homework policy: Late submissions will not be considered.
  • The homework with lowest score will be dropped when calculating the final grade.
  • Collaboration is allowed for all problems on your homework sheet, please list all the people with whom you discussed. Crediting help from other classmates will not take away any credit from you. However, only insightful discussions are allowed and it is not allowed to share or ask for the entire solutions and steps. The Honor Code is taken very seriously in this course and we have no tolerance for behavior that falls outside our boundaries for acceptable conduct. Please do your part in maintaining a community where academic work is done with a high standard of integrity.
  • Exams will be in-person or online, depending on the situations. The specific time and form will be announced later.
  • Absences: Make-up exams will only be allowed under extraordinary and unavoidable circumstances. Appropriate documentation verifying the absence may be required; in cases of illness, you will be asked to have official documentation from a physician-reviewed and verified by the Dean of the school. Make-up exam arrangements will be made based on a case-by-case basis.
  • Assignments and due dates will be announced on the course website. There will be reminders of the coming deadlines at the beginning of each week in our WeChat Group and/or via email.
  • Plagiarism will be dealt with severity. See “Academic Integrity” below for more details.
  • Grading clarifications (in assignments as well as exams) should be resolved within a week from the date when the graded submission is returned. No clarification applications will be considered after a week. Bring your clarification requirements to the TA’s office hour.

Regrade requests

Credit for work will be recorded only as reported by the TA in Blackboard. It is your responsibility to make sure that your work has been properly recorded in Blackboard.

If you need to request a regrade for an assignment, please adhere to the following policy:

  • If there was a clerical or math mistake in calculating or recording your grade, please go to office hours of the TA who graded it so that it can be fixed.
  • If you lost points for something you did correctly, e.g. the grader said “-2 points for not doing X” and you actually did do that (or something similar), please speak with the TA who graded it during their office hours. It is preferable to discuss these things in-person than over email. However, if you can’t attend the grader’s office hours, then email them to try to arrange another time to meet.
  • Likewise, if you lost points for something and do not understand the grader’s comments, please speak with the TA who graded it during their office hours if possible.
  • For any other issues, please contact the instructor. This may be things like “I didn’t realize we had to do X,” “I misunderstood this part of the assignment,” etc. This isn’t to say that you’ll necessarily get points back for your misunderstanding, but issues such as these should be discussed with the instructor.

Regrade requests must be made within one week of the score being posted in blackboard. Only regrades related to administrative mistakes (e.g., miscalculating the score or entering it incorrectly) made after the one-week period are likely to be considered.

Suggestions

  • Check wechat group for announcements! Check wechat! Check wechat! I mean, check your wechat group or cuhksz email, at least once a day.

  • Email TAs for homework-related questions (can either cc or not cc the instructor).

  • Email the instructor for other questions.

  • Check Blackboard and this website; e.g., once every 2-3 days.

  • Feel free to ask questions in the Wechat group. No question is stupid!

  • You can email the instructor for most questions regarding course contents or logistics, but the instructor may or may not be able to respond in time (though the instructor often replies within 24 hours). It is recommended to ask questions in the Wechat group, or email the TAs (you may consider cc the instructor). If it is urgent or you really want to hear from the instructor, you can add “[MAT2041 Urgent]” or “[MAT2041 Need Response]” to the title, so that the instructor will pay attention to the email. · You are encouraged to discuss lecture materials, practice problems with each other; but not homework problems.

General Course Policies:

Academic Integrity: Academic dishonesty may result in a failing grade (i.e. F). Every student is expected to review and abide by the Academic Integrity Policy of CUHK-Shenzhen. Ignorance will not be allowed as an excuse for any academic dishonesty. Do not hesitate to ask me if you are ever in doubt about what constitutes plagiarism, cheating, or any other breach of academic integrity.

Attendance requirement

You are expected to attend the course in-person(don’t wait until the last minute of the assignment deadline). We use quizzes help you keep the pace. Important course announcements will be made in Blackboard and this website or via email; you are responsible for being aware of these announcements.