Syllabus
1. Instrument architecture and PLC programming - Communication protocols used at large scale infrastructures
2. Communication with 6-axis robotic arm
3. Computer Vision - Object recognition, evaluation 2D images from microscope
4. Machine learning basics
5. Artificial intelligence and expert systems
6. Automatic planning of experiments
7. Bayesian optimization of measurements
8. AI driven data analysis
9. Publishing the data - F.A.I.R. principles - Describing data by the scripts - Storing data for generations
10. Future trends in automation - Using of the Large language models for writing papers
Annotation
The lecture will cover the role of automation and robotics in data treatment, including automatic data acquisition and analysis, machine learning, and artificial intelligence. The gained knowledge has direct application in materials science, quantum physics or research on large infrastructures.
We will also touch on large language models and how to use them efficiently. In fact, this annotation and syllabus are written by ChatGPT :).
Very basic knowledge of Python is expected. The course is suitable for all grades, English is possible.