- VBCF courses - lists.vbcf.ac.at

[VBC-SCIENCE] Curve fitting course announcement
by Aszodi,Andras April 14, 2026

April 14, 2026

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

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[VBC-SCIENCE] ANOVA course announcement
by Aszodi,Andras April 7, 2026

April 7, 2026

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

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[VBC-SCIENCE] Linear regression course announcement
by Aszodi,Andras April 1, 2026

April 1, 2026

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

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[VBC-SCIENCE] Visualisiation with ggplot course announcement
by Aszodi,Andras March 17, 2026

March 17, 2026

Dear Colleagues, I have the pleasure to announce my "Scientific Visualisation with ggplot" course. The aim of this course is to teach you how to create informative scientific plots using the ggplot package in R. For more details see https://training.vbcf.ac.at/training/rggplot.php . WHEN? Thursday the 26th March, from 09:00 to 13:00. WHERE? In person by default, in the IMP seminar room E-016. If you get (moderately) sick, you may participate online via Zoom, no need to cancel your participation. WHAT? • Fundamentals of scientific visualisation (this is not ggplot-specific but very useful). • Introduction to ggplot. Data preparation, plot creation workflow. • ggplot details: bars, boxes, densities, function plots, faceting (subplots). PREREQUISITES: Basic familiarity with R. Having attended my R language course ( https://training.vbcf.ac.at/training/rlang.php ) is an advantage. HOW MUCH? 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 page, click on the "Register" button for the ggplot course and fill out the little form. You will get an automatic acknowledgement by email, and an official confirmation from me later this week. NUMBER OF PARTICIPANTS: Limited to 12 in-person participants due to seminar room size. But I will organise an "overflow" course if needed. GENERAL RULES: please review them carefully at https://training.vbcf.ac.at/training/practical_information.php . Best regards, András You are receiving this message because you are subscribed to the VBC Science mailing list. To unsubscribe from this list, go to here<https://myaccount.microsoft.com/groups/64dd6714-c5a4-4ec9-a794-e7d168bf2f88> and select "Leave". If you want to re-join at a later time, visit this link<https://myaccount.microsoft.com/groups/search> and search for "VBC List" groups to join.

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[VBC-SCIENCE] Clustering and Classification course announcement
by Aszodi,Andras March 9, 2026

March 9, 2026

Dear Colleagues, I have the pleasure to announce a refurbished and extended "Clustering and Classification with Python" course, part of my "machine learning"/"advanced statistical modelling" collection. The course provides a short introduction to the huge subject of clustering and classifying observations. We will apply these tools e.g. to discriminate between healthy and diseased states based on example genomic datasets. For more details visit https://training.vbcf.ac.at/training/pyclassif.php . Topics: - Hierarchical clustering, k-means clustering. - Gaussian mixtures, E-M algorithm. - Quadratic and linear discriminant analysis. - Principal Components Analysis (PCA). - Cross-validation techniques. - Logistic regression and its connection with discriminant analysis. Multinomial regression. Out of scope: We can cover only basic methodologies. I have no resources to discuss analysis of private data sets during the course. When? Two half-days on the 19th and 20th March (Thu-Fri), from 09:00 to 13:00 on both days. Where? IMP seminar room E-016. Pre-requisites: - Proficiency in Python. https://training.vbcf.ac.at/training/pylang.php - Familiarity with NumPy, Pandas (https://training.vbcf.ac.at/training/pydata.php) and a little bit of MatPlotLib. - Solid probability theory and statistics knowledge. - Knowledge of basic linear algebra concepts: vectors, matrices etc. Cost: Free of charge. How to register? Make sure you don't have any meetings on the days of the course. Then ask your boss for permission to attend, and sign up at https://training.vbcf.ac.at/training/schedule.php by filling out the little form. Sign up only if you are confident that you will attend, don't take away a slot from a colleague. Consult the general attendance rules at https://training.vbcf.ac.at/training/practical_information.php . You will get a confirmation from me later this week. Thank you, András

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[VBC-SCIENCE] NumPy/Pandas course announcement
by Aszodi,Andras Feb. 16, 2026

Feb. 16, 2026

Dear Colleagues, I have the pleasure to announce the World Premiere of my new "Python scientific data packages" course (see https://training.vbcf.ac.at/training/pydata.php ). This course teaches you how to use the NumPy and Pandas packages which are the foundations of scientific computing in Python. Knowledge of NumPy and Pandas is a pre-requisite for my upcoming machine learning courses. Please read the following information carefully to the end. DATE/TIME: 27th February (Friday), 09:00 - 13:00. Please check your calendar and sign up only if you can attend. Do not take away slots from others by signing up and then not joining. TOPICS: NumPy: - Array creation. - Array indexing. - Array manipulation: reshaping, adding/removing rows and columns. - Broadcasting and universal functions ("ufunc"-s). - Text and binary file input/output. Pandas: - Series and DataFrame objects. - Object creation, data input/output. - Indexing. - Adding and removing rows and columns. Rearranging tables. Sorting. - Numerical work: aggregate functions, simple statistics, random samples. OUT OF SCOPE: - No data analysis. PREREQUISITES: - Python programming experience. The Python programming course (https://training.vbcf.ac.at/training/pylang.php) held just before offers a good foundation. COST: Free of charge. NUMBER OF PARTICIPANTS: Strictly limited to 20. First come, first served. HOW TO REGISTER: Ask your supervisor for permission to attend, then open this URL: https://training.vbcf.ac.at/training/schedule.php . Click on the appropriate [REGISTER] button. Then fill out the registration form. Please specify your job type correctly. Use an Austrian academic email address. See https://training.vbcf.ac.at/training/practical_information.php for details. Thank you, András

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[VBC-SCIENCE] Python programming course announcement
by Aszodi,Andras Feb. 13, 2026

Feb. 13, 2026

Dear Colleagues, I have the pleasure to announce my "Python programming" course (see https://training.vbcf.ac.at/training/pylang.php ) Please read the following information CAREFULLY TO THE END TO AVOID DISAPPOINTMENT. COURSE DIFFICULTY: This is an "entry-level" course that starts from the very basics of Python programming. However, towards the end we will move to more complex concepts. Please DO READ the "TOPICS" section below carefully! DATES/TIMES: The course consists of two parts, and both parts involve two four-hour sessions (16 hours in total). You must take both Part I and Part II because they build on each other. PART I: 23rd and 24th February (Monday-Tuesday), 09:00 - 13:00 PART II: 25th and 26th February (Wednesday-Thursday), 09:00 - 13:00 PLEASE DO CHECK YOUR CALENDAR BEFORE SIGNING UP! Make sure you can attend ALL sessions. Do not take away slots from others by signing up and then not joining. EXERCISES: There will be "homework" assignments after Days 1,2,3 so plan about 1-2 hours for them in the afternoons/evenings to work on them at your own pace. TOPICS: Day 1: - Introduction to Python: basic principles. - Python data structures: strings, tuples, lists, dictionaries, sets. Day 2: - Object-oriented programming in Python. Encapsulation, inheritance (base and derived classes), polymorphism. Day 3: - Writing a Python class and a small package using test-driven development techniques. Day 4: - Writing Python scripts. Command-line option processing, file I/O, error handling. OUT OF SCOPE: - No data analysis! This course is only about the Python language itself. - No personal projects! You all will work on the same task (genomic region manipulation). I don't have the resources to supervise individual projects. PREREQUISITES: - You must have good typing skills, otherwise you'll hold up everybody else. - Previous experience with another programming language is highly desirable (but not mandatory). COST: Free of charge. NUMBER OF PARTICIPANTS: Strictly limited to 20. First come, first served. Please sign up only if you can attend all four sessions! HOW TO REGISTER: Ask your supervisor for permission to attend, then open this URL: https://training.vbcf.ac.at/training/schedule.php . Click on the [REGISTER] button of Part I of the course, this will register you to Part II as well. (It is not possible to register for only one part.) Then fill out the registration form. Please specify your job type correctly. Use an Austrian academic email address. See https://training.vbcf.ac.at/training/practical_information.php for details. Thank you, András

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[VBC-SCIENCE] Basic statistics course announcement
by Aszodi,Andras Feb. 2, 2026

Feb. 2, 2026

Dear Colleagues, I have the honour to announce my "Think statistics!" course (more info at https://training.vbcf.ac.at/training/rstat.php ) The main aim of this course is to teach you to how to approach data analysis problems with classical statistics. We will focus on the intuition behind statistical methodologies, rather than on mathematical details. TOPICS: - Sampling theory: obtaining information about a population via sampling. Sample characteristics (location, dispersion, skewness). - Central Limit Theorem and the Normal distribution. - The distribution of the sample mean. Confidence interval of the mean. - Basic principles of hypothesis testing. "Student"'s t-test. - Type I and Type II errors. P-value distributions. Power calculations. - "Cookbook of tests": distribution tests (Shapiro, Kolmogorov-Smirnov), parametric and non-parametric tests (e.g. Wilcoxon), counting statistics, contingency tables (chi-square test), correlation tests. OUT OF SCOPE: Individual data analysis. SCIENTIFIC PREREQUISITES: - Basic probability concepts. - Working with (continuous) probability distributions. PROGRAMMING KNOWLEDGE: Basic familiarity with R is of advantage but not mandatory. It helps to understand the hands-on examples and to complete the homework assignments after Day 1. DATE/TIME: 11th-12th February (Wednesday-Thursday), from 09:00 to 13:00 on both days. Please reserve some time in the afternoon for the voluntary homework assignment. LOCATION: IMP seminar room E-016. Remote attendance is offered to colleagues outside the VBC. COST: free of charge. HOW TO REGISTER: 1) Check your calendar. *** If you register but don't attend, you are taking away a place from a colleague! *** 2) Ask your supervisor for permission to attend. 3) Inform your supervisor that you won't be available during the course. (No last-minute forgotten lab meetings etc! :-) ) 4) Open this URL: https://training.vbcf.ac.at/training/schedule.php Click on the [REGISTER] button and fill out the form. Use an Austrian academic email address. Please specify your job type (e.g. “PhD student”) correctly. Thank you, András

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[VBC-SCIENCE] Probability theory course announcement
by Aszodi,Andras Jan. 27, 2026

Jan. 27, 2026

Dear Colleagues, Trying to get ahead in science without speaking English? It won't work. Trying to get ahead in science without understanding probability theory? It won't work either. These are already two good reasons to attend my "Probability Theory" course (more info at https://training.vbcf.ac.at/training/rprob.php ). We will focus on the intuition behind probability theory rather than on a mathematically rigorous presentation. The knowledge taught in this course is a pre-requisite to my "Think statistics!" course (https://training.vbcf.ac.at/training/rstat.php ) which will be held on the 11th and 12th February. Topics: - Foundations of probability theory: basic identities (sum rule, product rule). Independent variates, conditional probability. - Discrete probability distributions: Uniform, Bernoulli, Binomial, Poisson, Negative Binomial. - Continuouos probability distributions: Uniform, Exponential, Gamma etc. - Central Limit Theorem. Normal and Chi-square distributions. Out of scope: Applied data analyses. Prerequisites: Knowledge of the 4 arithmetic operations. Basic familiarity with R is not needed but useful to understand the hands-on examples. Date/time: Tuesday 3rd February, 09:00 - 13:00h. Location: IMP seminar room E-016. Cost: free of charge. How to register: Check your calendar. If you register but don't attend, you are taking away a place from a colleague! Ask your supervisor for permission to attend, then open this URL: https://training.vbcf.ac.at/training/schedule.php Click on the [REGISTER] button and fill out the form. Please specify your job type (e.g. “PhD student”) correctly. Thank you, András

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[VBC-SCIENCE] R programming language course announcement
by Aszodi,Andras Jan. 21, 2026

Jan. 21, 2026

Dear Colleagues, I am pleased to announce my "R as a Programming Language" course (more info at https://training.vbcf.ac.at/training/rlang.php ). This introductory course serves as the foundation for my biostatistics trainings and teaches you the basics of the R programming language. Please read the following information carefully until the end. Who may attend? If you have received this email, you may sign up :-) Topics on Day 1: • Introduction to R: general principles. • Data structures in R: vectors, matrices, arrays, lists, data frames. Data import/export. Topics on Day 2: • Functions in R: how to write your own functions and scripts. • Visualization in R: various plot types ("classic" built-in graphics only). Out of scope: We won't discuss statistics at all. Basic biostatistics and more advanced data analysis/machine learning courses will come later. Prerequisites: Good typing skills. Experience with other programming languages is advantageous but not needed. Date/Time: 29th and 30th January (Thu-Fri), 09:00 - 13:00 on both days. Attendance: physical only, no remote participation. Reason: it's very difficult to correct typos over Zoom. Cost: free of charge. How to register: 1) Check your calendar. *** If you register but don't attend, you are taking away a place from a colleague! *** 2) Ask your supervisor for permission to attend. 3) Inform your supervisor that you won't be available during the course. (No last-minute lab meeting presentations etc!) 4) Open this URL: https://training.vbcf.ac.at/training/schedule.php Click on the [REGISTER] button and fill out the form. Please specify your job type correctly. Thank you, András VBCF Computational Biology Training Expertise Hub Course schedules: https://training.vbcf.ac.at/training/schedule.php RSS feed: https://training.vbcf.ac.at/rss.php See also: https://www.viennabiocenter.org/vbcf/computational-biology-training/ Contact: andras.aszodi(a)vbcf.ac.at You are receiving this message because you are subscribed to the VBC Science mailing list. To unsubscribe from this list, go to here<https://myaccount.microsoft.com/groups/64dd6714-c5a4-4ec9-a794-e7d168bf2f88> and select "Leave". If you want to re-join at a later time, visit this link<https://myaccount.microsoft.com/groups/search> and search for "VBC List" groups to join.

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