MATH 265 Linear Algebra
Section 185, Spring 2017
Course Information

Instructor: Guang Lin
Office hours: TR
01:1502:00pm (tentative) or by appointment
Email: guanglin [at] purdue.edu
Grader Tianran Liu, email: liu1121@purdue.edu

Announcements
You are welcome to apply for Network for
Computational Nanotechnology (NCN) Summer Undergraduate Research Fellowships to
work with me in summer on Machine Learning for Big Data using the Linear
Algebra you learned from this class:
https://nanohub.org/groups/ncnsurf
https://nanohub.org/groups/ncnsurf/ncnresearch

Textbook:
Elementary Linear Algebra Package Purdue University, Bernard Kolman

Fillin lecture notes in Python Interactive Jupyter
Notebook:
https://github.com/PredictiveModelingMachineLearningLab/MA265
Fillin Lecture notes in PDF format:
Jan. 1012 

Jan 1719 

Jan 2426 

Jan 31Feb 2 

Feb 79 

Feb 1416 

Feb 2123 

Feb 28Mar 2 
Prac 
Midterm I 

Mar 79 

Mar 2123 

Mar 2830 
Review 

Apr 46 
Prac 
Midterm II 

Apr 1113 

Apr 1820 

Apr 2527 
Review 
Prac
Final 

Lectures Time and Location
Section 185: TR
12:0001:15pm
Classroom: REC 123

Course Guide
Please refer to the Math Department
math265 homepage for general course
information such as textbook, homework, exam and grade policy.

Midterm and Final Exam:
Throughout the semester,
there will be two Midterms and one Final Exam. Midterms are in class. The final
exam is in the Final Exam Week. The date and the location will be announced
later in class.
Calculators are NOT
allowed in quizzes and exams.

Special Rules for this Section:
1. Most HW is submitted online at WebAssign by
Thursday evening 11:59pm. The few problems not submitted online, including all Matlab problems, will be collected every Thursday in the
beginning of class.
2. No late homework will be accepted.
3. Homework must be readable and, must be stapled
and Matlab HW is required to be printed. Illegible
scribblings will receive no credit from the grader.
4. Quizzes will be randomly given in the last 1015
mins in class. Most questions of quizzes will come from problems of previous HW
(or their variations).
5. The worst 4 online homework scores will be
dropped.
6. Actively participating in class and working on
extra credit problems will help improve your grade.
7. Grades may be curved according to instructor
discretion.

Syllabus

Homework:
Homework for this course
consists of two types: online homework and handgraded homework. The online
homework is based on the WebAssign system. Most online homework is due Thursday evening 11:59pm. The handgraded problems come from two resources:
textbook problems and Matlab projects. Handgraded
homework will be collected every Thursday in class. Weekly homework assignment
will be available at WebAssign system.
No late homework will be
accepted.
Homework should be
readable and stapled. Illegible scribbling will receive no credit from the
grader. For Matlab projects, you should hand in the
printout of your Matlab session, including the source
code and the generated graphs. You are encouraged to discuss with your
classmates. However, your writeup must be independent. Homework assignments of
high similarity will receive no credit.
Weekly homework
assignments can be found in the assignment sheet and webassign.

Grading Policy:
Homework assignments and quizzes: 25%
Midterm Exam I: 20%
Midterm Exam II: 20%
Final Exam: 35%
Scores of handgraded
homework assignments, quizzes and exams will be published on Webassign.
Late homework will not
be accepted
Academic dishonesty are prohibited
The worst 4 online
homework scores will be dropped.

Useful Links:
Department
of Mathematics, Math265 homepage
WebAssign
Blackboard
Department of
Mathematics