© PoL
Dear students, postdocs, and colleagues of sunny ☀️ PoL,
Beginning of August, August 7th. – 14th., Physics of Life (PoL) is running a new series of Data Analysis Workshops, again presented by the one and only Caltech Teaching Professor Justin Bois.
==> Two Courses: This year, we are not running one, but two (!) three-day courses on data analysis:
Course I: Statistical Inference in Physical Biology
07.– 09. August, intermediate level, location: CRTD SR3, 9:30 am - 5 pm
Course II: Bayesian Data Analysis
12. - 14. August, intermediate-advanced level, location: CRTD SR3, 9:30 am - 5 pm
Whatever your level — from Master's student to group leader — this is your chance to learn data analysis of biological data from one of the world’s best teachers (according to Rob Philipps)! Here is an overview of the course material from last year’s workshop (similar to Course I).
==> Register: We have around 30 spots each!!! First come, first serve. Please forward this to interested students and PostDocs who fulfill the requirements (intermediate Python / full-time commitment for the course). For registration, please reply with “Hurray, I’m interested in Course 1 (or 2, or both)!” or send a similar joyful message to marcus.jahnel@tu-dresden.de until next Wednesday, July 24.
==> Requirements: Importantly, these are intermediate courses! It will cover data analysis, data visualization, statistical inference, and parameter estimation using Python. An intermediate level of Python is required for both. If you used Jupyter Notebooks and have heard of Pandas data frames you are good to go! If you never used Python before (What? What are you waiting for?), and nonetheless really, really, really want to take part, then you have some time to get a Python crash course here: Link. This also works great as a refresher. You would need to go at your own pace up to around Lesson 15 to follow Workshop Course I.
The second requirement is that you are committed to joining for the whole duration of the courses, which consists of three full days each, 9:30 to 5 pm. Depending on demands and availability, there could be data discussion sessions at the end of each course, where you can discuss your data analysis challenges.
Happy Hacking & Learning!