Math 36600: Course Information

Course Title: Introduction to Applied Mathematical Computation

Prerequisites: Math 34600 and CSC 10200 or 10300.

Catalog Description: Calculus, linear algebra, elements of probability theory and combinatorics are examined through use of Matlab. Topics selected from symbolic and numerical problems in analysis; matrices, linear mappings, eigenvalues and applications; queueing theory; random numbers and simulations; graphics.

Semester: Fall 2020.

Section: F.

Meeting time and place: MoWe 3:30-4:45pm online via Blackboard Collaborate.

Instructor Information:
Course Textbooks: All texts above are available as a free download from the City College library. Please follow the links above. You will need to sign in to download the books.
Notice of Deviation from Catalog Description: While the Catalog Description of the course says that we will use MATLAB, this section of the course will primarily use Python instead. Please let me know by the second class meeting if you take issue with using Python. By remaining in this section of the course and not discussing this with Prof. Hooper, you agree to use Python rather than MATLAB.
Why Python? Python is a more broadly applicable programming language than MATLAB, and it us used by famous and important companies. It is widely used in Data Science. It is also free. You can install MATLAB for free on your computer because CUNY reached an agreement with the publisher of MATLAB, but it will no longer be free when you graduate. In additon, Python is open-source and has a large active community of users. In general, I believe it is much more valuable progamming language to learn than MATLAB. The following website gives a more comprehensive analysis along these lines:

General expectations: This is a challenging course. This course requires prior understanding of Linear algebra, Calculus, and Differential equations. (Though a differential equations course is not a prerequisite, some differential equations should have been covered in your Linear Algebra course.) You should also have some experience with computer programming. We will be using Python, but prior experience with Python is not necessary.

Proofs are a fundamental part of both mathematics and programming. You are expected to be able to write basic proofs of mathematical statements, and proofs related to algorithms. The claim that an algorithm terminates or returns the correct solution requires proof.

For each hour spent in the classroom, I expect you to spend at least three hours reading and understanding the book, understanding lecture notes, doing homework, and programming. Practice (doing problems, proofs, and programming) is an important part of learning. Only adequate practice will guarantee that you can complete midterm and final exam problems in a timely manner.

The best way to learn something well is to find something that interests you and do it. As we move through the course, try to find applications of the ideas to things you are interested in.

Expectations of written work: Mathematical computations, proofs, and programs will be graded partially on presentation. In order to receive full credit, a student who reads your answer should be able to easily understand how you solved the problem. Written work is expected to be legible and arguments are expected to be well articulated.
Grades: Grades will be computed from the following weighted average: Your final score will be tabulated out of 100% as indicated by the percentages above. A letter grade will be assigned to you according to the following list: A+ (97-100), A (95-96), A- (90-94), B+ (87-89), B (84-86), B- (80-83), C+ (77-79), C (74-76), C- (70-73), D (60-69), F (0-59).

Exam grade: Your exam grade will be determined based on your Final Exam grade and your midterm grades. Midterms contribute equally to the Exam Grade, while the Final exam contributes twice as much as a single midterm. For example, if you take two midterms and the Final Exam, then your Exam Grade will be determined by your Final Exam (50% weight), the first midterm (25%) and the second midterm (25%). This would make the final exam count for 20% of your course grade while the midterms each count 10%.

Midterm exam: There will be one midterm exam. It will be held on Wed, Oct 21. You will be given the full class to complete the midterm.

Final exam: The final exam will be held at a time determined by the college. As of the writing of this document, this time has not been determined.

Makeup exam: A final exam missed well-documented and sufficiently compelling circumstances will result in a the offer of a makeup being given. The makeup must be taken within one week of the scheduled exam, or a zero will be assigned as the exam grade. Notify me ahead of any exam you expect to miss to be sure your circumstances are sufficiently compelling.

Proctoring: This course may employ an online proctoring system for exams, which may require the use of a video camera.

Homework assignments: Homework will be assigned approximately once a week and will have a due date. Homework assignments will be made available on the course website at least one week before the assignment is due. I encourage you to work in groups on the homework problems, especially if this best suits your learning style. Nonetheless, you should be confident that you understand how to do each problem, and should be able to solve similar problems independently. Failure to ensure that you can solve problems independently will surely have a negative effect on exam grades.
Late homework: Late homework will not be accepted for any reason.
Dropped homework grades: The two lowest homework grades will be dropped.
Final Project: Details on the project will be announced midway through the semester. The project will likely involve using techniques developed in the course to analyze some publicly available data of your choosing.
Course website: Course information, homework assignments, and documents can be found on the website:
Blackboard: I use blackboard to keep track of your grades. You can view your grades there. To access blackboard visit: I will likely use blackboard collaborate for class meetings.
Academic integrity: You are expected to adhere to the CUNY Policy on Academic Integrity. This policy is posted at In particular, it is expected that you not plagarize. This has been especially problematic on homework. Your homework must not copy from another source, and you must cite any sources used when preparing your solutions. Sources can include textbooks, webpages, discussions with other people, and other student work. Citations should be as specific as possible. All submitted work must be written in your own words.
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