|Course title||Computational Physics|
|Status||Lectures(15), Seminars (30), Exercises (15)|
|Lecturer||Dario Hrupec, Assistant Professor
Igor Miklavčić, Lecturer
|Course objective||Numerically solve and graph physical problems using a computer.|
|Prerequisites||Computer Laboratory (code I116)|
|Learning outcomes:||After successfully completed course, student will be able to
|Teaching activity||ECTS||Learning outcome||Students’ activity||Methods of evaluation||Points|
|Class attendance||1||1-10||Attends classes||Evidence list||0||15|
|Independent exercises of program codes writing||2||1-10||Solves weekly individual exercises||Weekly scoring of independent work||0||45|
|Final exam||2||1-10||Modifies a program code in order to get required new functionality||Oral exam||0||40|
David Pine, Introduction to Python for Science and Engineering, CRC Press, 2019.
Eric Ayars, Computational Physics with Python, 2013.
Ben Stephenson, The Python Workbook: A Brief Introduction with Exercises and Solutions, 2nd Edition, Springer, 2019.|
Zvonko Glumac, Računalne metode fizike: kratak uvod, 2015.
|Instructional methods||One hour of lectures, two hours of seminars and one hour of exercises per week. Students actively participate in classes so that, each on their own computer, writes, tests and corrects their own program code for a given problem.|
|Exam formats||Every week, a student get an individual excercise that needs to be solved independently and which is graded. At the final oral exam, a student modifies given program codes in order to get a new program functionality.|
|Quality control and successfulness follow up||Student survey|