Mathematical Models, Fall 2019
Syllabus

Course: Math 245, Fall 2019.
Instructor: Christopher Hanusa — Email: chanusa@qc.cuny.edu — Office: Kiely Tower, Room 606
Meeting Times: Mondays and Wednesdays from 1:40–2:55 in PH 212.

Course Web Site: http://qcpages.qc.cuny.edu/~chanusa/courses/245/19/
Course File Repository: On Google Classroom. You may first need to log in to your QC Google Account and access Google Classroom from there. Our course code is dlu8ely.
Course Discussion Board: On Google Groups. You may first need to log in to your QC Google Account and access our Google Group from there.

Textbook: Modeling and Simulation in Python, by Allen B. Downey (Version 3.4 as of August 2019.) The electronic version of the textbook is free; if you want a physical version you can order one from Lulu.
Notebook: Acquire a 50-80 page notebook to use as a Homework Notebook. Don't forget to write your name and contact information on the inside cover.
Software: Python, either online with Azure Notebooks or on your own computer with Anaconda.

Class Participation:

Succeeding in this class will require your participation. You will earn a class participation grade based on your attendance and your participation. A great way to participate is to ask questions. A question as simple as "I don't really understand how/why you did X; can you explain it in a different way?" is a great question to ask and it shows that you are involved in the class.

You are expected to participate on the course discussion board by asking questions and answering your classmates' questions. You will participate in the in-class activities, our group discussions, and by discussing the tutorials with your neighbors. If you miss a class, you are responsible for the material you missed—get the notes from your classmates and study group and make sure that you understand the material that you missed.

Homework Policy:

You are expected to be working outside of class. The Course Content page lets you know what is expected. Your homework will consist of practicing the content we have discussed in class, getting hands-on experience with coding in Python, doing some pre-reading about the concepts that will be appearing in class in the near future, and making progress toward your group projects. It will be normal that you spend many hours of work to understand small details, and that is why working in study groups is so rewarding. As in any class, you will need to put in the time to fully understand the concepts.

The homework that you complete should be done in your homework notebook; I will collect these notebooks on random days throughout the class and this will count toward your homework grade. Start each page in your homework notebook with the date and the question number that you are answering. I also suggest creating a section where you compile a list of questions to ask your professor and your fellow students as you go along.

Study Groups:

An important component of your learning in this class is through study groups. Study groups allow you to learn the intricacies of the material; discussion of problems often lead to better understanding and new and more efficient ways to solve the problems. One of the best ways to learn something is to explain it to someone else; misunderstandings that you never knew you had will appear under someone else's questioning! In addition, seeing that others also struggle with the material helps to put your own level of understanding in a better perspective and will hopefully reduce some of your anxiety. If you can not find a study group, e-mail me so that I can help you get involved.

Most importantly, I assume that you will be working in groups when I make up the homework assignments. When a group works on a problem, everyone can participate. But when you write up the answers to the problems, write it up in your own way. And it is always nice to acknowledge your groupmates in your notes.

Grading Scheme:

Your grade will be based on class participation, homework, and your projects. Each component of your grade is calculated independently; then all pieces are combined using the following weighted average.

Participation and Homework Checks: 15%
Mini-Project 1: 20%
Project 2: 30%
Project 3: 35%

Office Hours:

I am happy to help you with your homework and other class-related questions during my office hours. Office hours will be determined by group consensus during the first week of class and will be announced in class and posted on my schedule. In addition, you are welcome to make an appointment or stop by my office in Kiely Tower Room 606 at any time. (You can call 718-997-5964 to see if I'm there.)

Cheating/Plagiarism:

DON'T DO IT! It makes me very mad and very frustrated when students cheat. Cheating is the quickest way to lose the respect that I have for each student at the beginning of the semester.

Working together on homework and projects is encouraged and is certainly not considered cheating. On the other hand, copying someone else's work IS cheating.

I encourage you to download/explore/use other people's source code to learn about what is and is not possible to do using Python. However, copying content from online or offline sources and passing it off as your own work IS cheating. The work you turn in for your projects must be your own and include citations of any code that you use or inspired your project.

I take cheating very seriously. If you cheat, you will receive a zero for the assignment and I will report you to the academic integrity committee in the Office of Student Affairs to be placed on your permanent file. If you cheat twice, you will receive a zero for the class.

Accommodations for Students with Disabilities:

Students with disabilities needing academic accommodation should register with and provide documentation to the Office of Special Services, Frese Hall, room 111. The Office of Special Services will provide a letter for you to bring to your instructor indicating the need for accommodation and the nature of it. This should be done during the first week of class. For more information about services available to Queens College students, contact the Office of Special Services (718-997-5870) or visit their website (http://sl.qc.cuny.edu/oss/).

Course Evaluations

During the final four weeks of the semester, you will be asked to complete an evaluation for this course by filling out an online questionnaire. Please remember to participate in these course evaluations. Your comments are highly valued, and these evaluations are an important service to fellow students and to the institution, since your responses will be pooled with those of other students and made available online, in the Queens College Course Information System (http://courses.qc.cuny.edu). Please also note that all responses are completely anonymous; no identifying information is retained once the evaluation has been submitted.

Technical Support

The Queens College Helpdesk (http://www.qc.cuny.edu/computing/ — 718-997-4444 — helpdesk@qc.cuny.edu) is located in the I-Building, Room 151 and provides technical support for students who need help with Queens College email, CUNY portal, Blackboard, and CUNYfirst.