| Instructor | Prof. Qiang Zhu |
|---|---|
| [email protected] | |
| Website | http://www.physics.unlv.edu/~qzhu/ |
| Office | BPB 232 |
| Office hours | Mon/Weds 3:45 - 5:00 pm |
| Weeks | Subjects |
|---|---|
| 1 | Python basics I (installation, variables, list, loops) |
| 2 | Python basics II (function, advanced libraries) |
| 3 | Integrals/derivatives |
| 4 | Fitting/interpolation |
| 5 | Fourier transform |
| 6 | Random numbers |
| 7 | Monte carlo |
| 8 | Optmization I |
| 9 | Optmization II |
| 10 | Optmization III |
| 11 | Machine Learning I (algorithms) |
| 12 | Machine Learning II (applications) |
| 13 | Machine Learning III (database tools) |
| 14 | Machine Learning IV (online database) |
| Items | Percentage |
|---|---|
| Attendance | 10% |
| Problems and Quiz | 20% |
| Projects | 40% |
| Final Exam (oral) | 30% |
This course is open to all students who are interested in scientific programming and data analysis. It will teach students to write programs to solve simple physics programs on the computer and to manage their codes via github. There will be weekly assignments and two projects during the semester, plus an oral exam in the end of semester. Please bring your laptop to class. All the practices will be based on Python 3. Barring documentable emergencies or observance of a certifable regious holiday, all exams must be taken at the time and place specified.
In addtion to the code page, we also have a wiki page which has extended discussions on some focused topics. Most of them were created by the students.