Dear Colleagues,

"This is not my AI course", not yet. But if you want to understand neural networks, you need to learn about nonlinear regression first.
TOPICS
- How to fit a PCR curve? Simple nonlinear regression.
- Did my enzyme inhibitor work? Statistical comparison of several nonlinear regression models.
- More than one independent variable? Multivariable nonlinear regression.
- Non-parametric techniques: LOESS, kernel smoothing methods, splines, generalized additive models.
More details at https://training.vbcf.ac.at/training/rnonlinreg.php
When? 24th April (Friday), from 09:00 to 13:00.
Where? Physically at the IMP seminar room E-016. Non-VBC colleagues may attend online if needed.
Mandatory prerequisites: Basic statistics knowledge: "Think Statistics! with R" course https://training.vbcf.ac.at/training/rstat.php or equivalent.
Recommended: Familiarity with linear regression ( https://training.vbcf.ac.at/training/rlinreg.php ).
How much? Free of charge.
How to register? Check your calendar. Then head to https://training.vbcf.ac.at/training/schedule.php , click on the corresponding Register button and fill out the little form. Make sure your PI agrees to your participation. Please keep in mind that registration involves a commitment to attend.
General rules: Review them carefully at https://training.vbcf.ac.at/training/practical_information.php .
Best regards,
András
Dear Colleagues,
In scientific research we often compare the means of groups of observations. If you have never worked with data like this:

then it's just a matter of time and you definitely will :-)
This is why I am offering my "ANOVA with R" course which will teach you how to analyse such datasets.
TOPICS (see ANOVA course <https://training.vbcf.ac.at/training/ranova.php> for details):
The intuition behind ANOVA: Comparing the means of several samples by analyzing variances.
Technical details: prerequisites, omnibus F-test, post hoc tests.
Getting the sample size right: Power calculations.
The relationship between ANOVA and linear regression [optional].
Combination of effects: two-way ANOVA.
"Are these regression lines different?" ANCOVA [if we have time].
DATE/TIME: Friday the 17th April, 09:00 - 13:00.
LOCATION: "Live" at the IMP seminar room E-016 by default. Online participation via Zoom is available only as a fallback option.
PREREQUISITES: Familiarity with R and basic statistics knowledge. Attending my Linear Regression course <https://training.vbcf.ac.at/training/rlinreg.php> which is scheduled on Thursday 16th April is highly recommended as the two methodologies are intimately related.
COST: Free of charge.
HOW TO REGISTER:
First of all: If you register and then don't attend, then you take away a place from a colleague. Please plan ahead responsibly.
1) Check your calendar!
2) Ask your PI.
3) Go to the Training schedule <https://training.vbcf.ac.at/training/schedule.php> page, click on the "Register" button for the ANOVA course and fill out the little form. Note that the linear regression course registration is still open, please do not mix up the two! (But it's all right to attend both... :-) )
You will get an automatic acknowledgement by email, and an official confirmation from me later this week.
Thanks, András
Dear Colleagues,
* The "LLM Castle of AI" (vibe-painted by me personally, with Mr Claude's help) is based on transformer networks.
* Transformer networks are neural networks.
* Neural networks are nonlinear regression methods.
* Nonlinear regression is based on linear regression.
This means that linear regression is the cellar of the "AI castle".
Join me in exploring this cellar, which harbours no monsters or expensive wine, but some interesting topics, such as:
- How to fit straight lines? Single, weighted and multivariable linear regression.
- How to model noise in both variables? Orthogonal regression, Principal Components Analysis.
- How to simplify the models? LASSO, Ridge, Elastic Net regressions.
- What to do with correlated independent variables? Principal component regression, orthogonal polynomial regression.
More details at https://training.vbcf.ac.at/training/rlinreg.php
WHEN? 16th April (Thursday), from 09:00 to 13:00.
WHERE? Physically at the IMP seminar room E-016. Non-VBC colleagues may attend online if needed.
PREREQUISITES: Basic statistics knowledge. If you have attended my "Think Statistics! with R" course ( https://training.vbcf.ac.at/training/rstat.php ) then you are well prepared. Some very basic familiarity with R is also required.
HOW MUCH? Free of charge.
HOW TO REGISTER? Check your calendar. Then head to https://training.vbcf.ac.at/training/schedule.php , click on the corresponding Register button and fill out the little form. Make sure your PI agrees to your participation in the course. Please keep in mind that registration involves a commitment to attend.
GENERAL RULES: Review them carefully at https://training.vbcf.ac.at/training/practical_information.php .
Best regards,
András
