Advanced Programming Skills
Full course description
With the modernization and automation trends across all fields and professions, programming and coding skills become imperative for engineers. With more open-source programming languages and hardware becoming available, the step towards custom build set-ups and instrumentation is becoming ever smaller and more accessible.
This course is designed as a follow up course to Basic Programming Skills in year 1, where MATLAB is introduced. In this course, you learn how to use the open source programming and scripting language Python. By having to transfer your existing knowledge of MATLAB to Python, you deepen your understanding of both languages and it will lower the barrier to learning more programming languages in the future.
While developing skills in Python, you have to apply this knowledge by using common data analysis techniques, like visualization, smoothing, and fitting to generic and specific functions. In addition to data treatment, you learn how to use Python to program a Raspberry Pi in teams. The addition of data acquisition to your skillset enables you to tackle nearly all practical challenges engineering has to offer. The use of Raspberry Pi’s has increased enormously due to the potential it has to build custom set-ups. This can range from controlling sensors to measure e.g. temperature and/or pressures at given intervals or to program a control unit to automate entire experiments. This will especially be useful for circular engineers as the data they need to propose more sustainable processes is often not readily available or can be expensive to obtain with commercial devices.
Students who have completed this skills course will be confident to build a custom set-up for any purpose in their studies and beyond that during their career. You will be challenged to come up with creative solutions to problems by identifying what is the core of the problem and tackling exactly these.
Course objectives
At the end of this course, we expect you to be able to:
▪ Write scripts/functions with Python syntax/code, using targeted at data processing and visualization.
▪ Fit advanced curves, numerical and statistical analysis with Python.
▪ Write a simple program to run on the Raspberry Pi.
▪ Use the Raspberry Pi to control a given sensor.
Recommended reading
▪ Python Data Science Handbook: Essential Tools for Working with Data (2016), Jake VanderPlas, O’Reilly Media, USA.