FYSA1120 Physicist's Computing Toolbox (2 cr)
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Description
Basics of Python programming
Jupyter notebooks
Management of data files
Using arrays (NumPy)
Using scientific program libraries (NumPy, SciPy)
Handling of ASCII data
Data visualization using graphs and figures
Symbolic mathematics (SymPy)
Learning outcomes
Upon completion of the course, the student is able to do the following things with the Python programming language:
write simple programs for numerical problem-solving
process data arrays (NumPy)
perform simple statistical analysis and fit model to data (SciPy)
produce simple graphs and figures (matplotlib)
perform simple mathematical operations symbolically (SymPy)
transfer, edit, and use local and cloud-based data files in different format
Additional information
The course should preferably be studied at the same time as the experimental courses FYSP1081 and FYSP1082.
The course uses Jupyter notebooks and a web platform (such as TIM) that allows running Python code interactively.
Description of prerequisites
Basic skills in operating a computer
Basic knowledge of high-school-level physics and mathematics
Study materials
Lecture notes
Python language documentation
Numpy, SciPy, SymPy and matplotlib documentation
Completion methods
Method 1
Independent study (2 cr)
Project work.