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Fall 2023

Linear Algebra and Programming (선형대수및프로그래밍)

Instructor: Dr. Muhammad Syafrudin

Course information

This course will cover linear algebra, with an emphasis on its applications. Students will study the theory as well as practical examples/exercises in the Python programming language throughout the lectures. Students are expected to grasp the principles of linear algebra theory and its implementation in the Python programming language by the end of the course.

Lecture

Tue at 12:00‐15:00 am KST at 광910

Office hours

Appointment by email (Office at AI Center 502호)

Prerequisites

Familiar/has experience with basic math and programming experience

Notes

Course material can be downloaded in e-campus (집현캠퍼스) and please be aware, 
that we will not publicly release the homework assignments this year.

Please note that:
-All lectures are in English.
-Weekly lecture topics may be adjusted or changed without prior notice depending
on the understanding level during the class.
-All lectures will be conducted offline or online depending on the university regulations.
-We will notify you via e-campus (집현캠퍼스)/email if there is an update from the university regarding the class.

Please contact me or stop by my office if you have any issues with the course.

Schedule

주차(Week)강의내용(Class Topic & Contents)강의활동유형(Class Type)
1Course overview and introduction to python programming (9/5)강의 (Lecture)
2Vectors theory and in Python (9/12)강의+실습 (Lecture + Practice)
3Linear functions theory and in Python (9/19)강의+실습 (Lecture + Practice)
4Norm and distance theory and in Python (9/26)강의+실습 (Lecture + Practice)
5No class -- Public holiday: National Foundation Day (10/3)No class
6Clustering theory and in Python (10/10)강의+실습 (Lecture + Practice)
7Linear independence theory and in Python (10/17)강의+실습 (Lecture + Practice)
8Midterm exam (10/24)시험 (Exam)
9Matrices theory and in Python (10/31)강의+실습 (Lecture + Practice)
10Matrix examples theory and in Python (11/7)강의+실습 (Lecture + Practice)
11Linear equations theory and in Python (11/14)강의+실습 (Lecture + Practice)
12Linear dynamical systems theory and in Python (11/21)강의+실습 (Lecture + Practice)
13Matrix multiplication theory and in Python (11/28)강의+실습 (Lecture + Practice)
14Matrix inverses theory and in Python (12/5)강의+실습 (Lecture + Practice)
15Least squares theory and in Python (12/12)강의+실습 (Lecture + Practice)
16Final exam (12/19)시험 (Exam)

Grading

The final grade will be calculated using the following weights:

#Final Grade Weight
Attendance10%
Assignment(quiz/homework/weekly assignment)20%
Mid exam30%
Final exam40%
Total100%

Assignment

There will be a quiz/homework/weekly assignment to complete. Some of them will be due in a week and some of them in two weeks. You have the option to work and submit the homework in pairs for all the assignments except two which you will do individually.

Submitting an assignment

Instructions for turning in assignments will be posted when the semester starts (in e-campus (집현캠퍼스)).

Getting help

For questions about homework, course content, installation, and after you have tried to troubleshoot yourselves, the process to get help is: Post the question in e-campus (집현캠퍼스)/group chat and hopefully your peers will answer. Note that in e-campus (집현캠퍼스) questions are visible to everyone. For private matters send an email to helpline: udin [at] sju [dot] ac [dot] kr.

Course Policies

Collaboration policy

We encourage you to talk and discuss the assignments with your fellow students (and on e-campus (집현캠퍼스)), but you are not allowed to look at any other students assignment or code outside of your pair. Discussion is encouraged, copying is not allowed.

Late day policy

Homework is due before each class. Late submission are not allowed.

Communication to students

Class announcements will be through e-campus (집현캠퍼스). All homework and quizzes will be posted in e-campus (집현캠퍼스). Also all feedback forms. Important note: make sure you have your settings set so you can receive emails from e-campus (집현캠퍼스).

Academic honesty

We give a strong emphasis to Academic Honesty. As a student your best guidelines are to be reasonable and fair. We encourage teamwork for problem sets, but you should not split the homework and you should work on all the problems together.