Programming for Data Science

The course treats basic programming concepts, such as:

1. program structures, including statements, expressions, defining and calling functions and data types; 
2. control flows, including sequential execution, conditions, loops, iteration, higher-order and recursive functions; 
3. data types, including data abstraction and classes such as lists, arrays and dictionaries; 
4. principles for code reuse, e.g. functions, objects, arguments, scope and return values; 
5. basic concepts of object orientation, e.g. classes, attributes, methods and inheritance; 
6. practical considerations when programming and implementing ideas, including algorithmic thinking, testing and use of program libraries.

The student develops practical skills through computer labs and practical programming tasks in the project. The course also includes a demonstration of “algorithmic thinking”, that is, going from an idea (in the form of a task description) to a sequence of steps, definition of input and output, division into functions or modules, etc. The students shall then apply this knowledge themselves in individual projects.