| CARVIEW |
Scientific Programming in 
The aim of this 5-day course was to provide an introduction to the Python programming environment for research students. The course will assume no prior knowledge about programming and will provide a general introduction to programming in Python as well as an introduction to capturing, exploring, analysing, and plotting data in Python.
This course was made possible with the support of the UCL Graduate School and Dr Mark Herbster.
The materials will still stay here should you want to go through them by yourself.
News
This course is not taught anymore. The last course was held in March 2017.Course content
- General introduction to programming
- Programming in Python
- Using the interpreter and iPython
- Writing Python scripts
- Loops and control flow (for-loops, if-statements)
- Data types: strings, lists, dictionaries
- Using and writing functions
- Matrices, Vectors, and Arrays: the Numpy package
- Functions for scientific programming: Numpy and SciPy
- Plotting and producing graphs: Matplotlib
- Debugging in Python
Prerequisites
In this course we will use the Anaconda Python distribution. This distribution contains many popular Python packages and will get you going in no time! We have prepared a complete installation guide for you, check it out in our help section.
In addition to the Anaconda Python distribution you also need to install a proper text editor (and we are not talking about Microsoft Word). We recommend Sublime Text 2, but check out the help section for some additional information.
If you have any questions or problems installing either Anaconda or a text editor please contact us!