Course content

The subject covers fundamental programming concepts as well as some more complex programs and applications within relevant fields.

Basic concepts: Variables and data types, operators, input and output, sequence, selection, repetition, functions, modules and libraries.

Data structures: Lists, tables, text strings, quantities, tuples, entries (dictionary), sorting and searching.

Data storage and error handling: File management, persistent information storage, and exception handling.

Data analysis and visualization: Representation of numbers, processing and visualization of measurement data, and iterative equations solution. Basic understanding and use of the modules NumPy and Matplotlib.

Applications: The areas of programming application focused on depending on the participants' wishes and case descriptions. Some areas that may be relevant to get into: Numerical derivation and integration, solving equations, simulation of dynamic systems, optimization, model adaptation to data, statistics and probability calculus, signal filtering and automatic regulation

Development environment: Jupyter Notebook is used as a programming environment.

Learning outcome

General competence

The course participants can include basic programming in their teaching: this means that the course participants, after the course:

• Can carry out smaller programming projects after the course.
• For small-scale problems, one can use the analysis process, find an algorithm formulated as pseudocode or flowchart, and then program a solution and test whether it works in Python.

The participants need sufficient knowledge and skills to achieve the competence goal described below.

Knowledge

To achieve the competence goals, the participants need sufficient knowledge of

• The basic elements of procedure-oriented programming
• The process from problem to working program includes knowledge of techniques and methods for testing and troubleshooting in simple programs.

Skills

In addition, participants should be able to:

• use data structures, control structures and decomposition in functions and modules to create well-structured and functional code
• use key numeric methods to solve computational problems, and import and use numeric library functions in Python
• Use relevant programming tools, such as Jupyter Notebooks or other syntax-driven editors with semantic error marking and step-by-step execution with a variable inspection.

Learning methods and activities

Programming fundamentals will be available for independent study. Video and other learning resources are made available, and participants are guided on relevant topics they must delve into before each seminar. The seminars will consist of lectures, reviews, and supervision of cases and group work.

Discussion forum: Mattermost is used as a discussion channel to get support from instructors, learning assistants and other participants.

Specific conditions

Recommended previous knowledge

Basic programming in Python

Course materials

"Python for realfag"

ISBN 9788245036695

Authors: Haugen, Finn Lysaker, Marius