Programming and Data Analysis

The objective of the course is to give a broad introduction into computational engineering methods, in particular the basics of:

• Data processing and statistical analysis
• Computer science
• Numerical simulation methods

The course is centered around a problem-based approach with practical programming exercises in Python.

In addition to the individual course topic, the study program shares a common project theme across all courses. This is addressed through the perspective and methodology of each course to deliver discipline specialization, as well as linking the different scopes and aspects into a holistic engineering view.

Course Curriculum:

• Data types, data structures, algorithms, operations, python basics
• Reading, writing and plotting of data
• Random numbers, computational statistics
• Time series analysis
• Frequency analysis
• Regression analysis
• Numerical solution of ordinary and partial differential equations
• Computer graphics
• Graphical user interfaces
• Spline fitting
• Rigid body motion simulation

Knowledge: familiar with the fundamental concepts of computer science and numerical analysis

Skills: programming with Python

General competence: analysis, mathematical modeling and numerical simulation of engineering problems

Lectures, exercises, homework assignment.