organized in cooperation with Helmholtz Information & Data Science Academy (HIDA) and Helmholtz AI
Introduction to Machine Learning
- ATTENTION: CHANGED DATES!-
This 4-day online course will introduce you to machine learning. The potential applications of ML and deep learning methods to natural science research are numerous, including detector development, data analysis techniques, and even physical modelling. These techniques will be essential to ensure the highest-quality and impactful scientific results from existing and future experimental works.
The basic course is for you if you do know Python and want to learn the basics of machine learning in a short block course. You may or may not join the intense study group afterwards to dive deeper into advanced topics. The introductory course will be based on scikit-learn and equip the participants with basic tools necessary to begin implementing and using ML methods. It will involve some theoretical descriptions but focus on hands-on exercises and discussions in the tutor group.
Learning Goals
After this course, learners can embark on classification and regression projects using scikit-learn and should be able to transfer their knowledge to other platforms, such as TensorFlow and PyTorch.
Prerequisites
If you want to enroll in this course, we expect you to bring along knowledge of the Python language, as taught in the courses "First Steps in Python" and "Data Processing with Pandas and Visualization with Matplotlib" (basic Python, Pandas, Matplotlib).
Target Group
This course targets researchers interested in machine learning.
Course Days & Times
June 16, 2025, 9 am - 5 pm
June 17, 2025, 9 am - 5 pm
June 18, 2025, 9 am - 5 pm
June 19, 2025, 9 am - 1 pm
NOTE: Registration will open May 19, 2025, 12 pm.
Attendance & Certificates
The course content is coordinated, so we strongly recommend that you do not miss any part of the course. To receive a certificate we expect full time and active participation.
Registration & Cancellation
This course is open to individuals affiliated with Helmholtz or a HIDA Partner only.
Your registration for this course is binding. If you need to leave/miss the course for a period of time, please let us know in advance via hida-courses@helmholtz.de.
If you have to cancel the course for any reason, please do so as soon as possible to allow time for others to take your seat. To cancel, please withdraw your registration on the course site or write an email to hida-courses@helmholtz.de.
Additional Information
There is no waiting list for this course! If someone withdraws from a course, their place is automatically reopened. We therefore advise you to keep an eye on the registration in case the course is fully booked and you would like to attend. Also, this course will be offered again in the future - you can check our HIDA course catalog for updates.
This course is free of charge.
