Upon completion of the course you should be able to:
Use basic coding concepts such as loops, control statements, variable types, arrays, array operations, and boolean logic. (LO1)
Write, run and debug programs in a high level language. (LO2)
Carry out basic operations (e.g. cd, ls, dir, mkdir, ssh) at the command line. (LO3)
Maintain a version controlled repository of your files and programs. (LO4)
Create publication/presentation quality graphics, equations. (LO5)
Visualize symbolic analytic expressions - plot functions and evaluate their behavior for varying parameters. (LO6)
Use numerical algorithms (e.g. ODE solvers, FFT, Monte Carlo) and be able to identify their limitations. (LO7)
Code numerical algorithms from scratch and compare with existing implementations. (LO8)
Read from and write to local or remote files. (LO9)
Analyze data using curve fitting and optimization. (LO10)
Create appropriate visualizations of data, e.g. multidimensional plots, animations, etc. (LO11)
The following are core, required resources for the course:
The following are optional, but highly useful, resources you might find useful:
ThinkPython: (http://www.greenteapress.com/thinkpython/) A free online Python textbook.
Python Scientific Lecture Notes: (http://scipy-lectures.github.com/index.html) Useful tutorials on using the Python scientific computing libraries.
Software Carpentry: (http://softwarecarpentry.org) Tutorials on scientific computing.
Your final grade in the course will be based on the following:
| Assignments: | 40% |
| Midterm Exam: | 20% |
| Project: | 40% |
This class is about building skills. The only way to build your skills is to practice them. Therefore, in order to receive a passing grade (C- or better) in this class you must pass/complete a minimum of 50% of the material in each grading category. How well you do in each of the categories will be used to determine your final letter grade. Do not ignore any of the exercises or assignments.
Assignments will be distributed and turned in each week using GitHub. The distribution of problems will be gradual throughout the week, but they will all be due on a single day. More details will follow. You will work on the problems both in and out of class, so class attendance is mandatory. You must stay until the end of class unless you get specific, explicit permission to leave early.
We will be spending our class time learning to code and solve physics problems numerically by doing hands-on activities at the computer. Sometimes you will work alone. Other times you will participate in pair programming exercises where you are the driver and your partner is the navigator and vice versa. Studies show that this is a very effective way to learn programming.
As with any skill, the only way to become proficient is to practice. A LOT. Think about your experiences learning a musical instrument or playing a sport. A little bit of practice every day is crucial. You will probably be spending 8 to 12 hours per week outside of class writing and debugging code.
If you have trouble with the homework, come to my office hours or seek help from your peers in person or or Gitter. Don't wait until you are in trouble to take action.
During week 6, you will be assigned an open-ended programming project provided by me. You will have until 11:59pm Friday of the tenth week of instruction to complete your project and submit the code to your PHYS 202 GitHub repository. We will spend some class time working on the projects but most of the work will be completed outside of class. Part of the project will be collaborative with other students assigned the same project, but you will be responsible for completing the coding, documentation and analysis assigned to you. Detailed instructions for completing the projects will be included in the project descriptions.
During the final exam period you will present a 5-10 minute demonstration of your project and its results to the rest of the class. The demonstration will be graded by me and your peers using an oral presentation rubric. These assessments will be part of your grade for the project.
Section 02: Wed, June 10, 10:10-13:00
Section 03: Monday, June 8, 13:10-16:00
You will be contacted by me if I suspect academic misconduct. Appropriate actions might include but are not limited to a failing grade on the assignment, a grade reduction in the course, or a failing grade in the course. See the Office of Student Rights and Responsibilities website for further information.
To help you remember to follow these guidelines, we will create a pledge file (called PLEDGE.md) in the main directory of your PHYS 202 GitHub repository. It is your signed contract stating that you have read and understand the rules regarding academic honesty and agree to abide by them.