README.md

Physics 300, Fall 2018

Introduction to Physics and Scientific Computing

Location: BPB-248

Schedule: Mon/Weds 2:30 - 3:45 pm

Instructor	Prof. Qiang Zhu
Email	[email protected]
Website	http://www.physics.unlv.edu/~qzhu/
Office	BPB 232
Office hours	Mon/Weds 3:45 - 5:00 pm

Course Outline

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)

Prerequisites: PHYS 152, PHYS 152L or PHYS 180

Credit Hours: 3

Textbook: Computational Physics, M. Newman (not required)

Grade Distribution:

Items	Percentage
Attendance	10%
Problems and Quiz	20%
Projects	40%
Final Exam (oral)	30%

Course Description

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.

Appendix

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.