Category: R

Spatial Data Wrangling with R workshop

Learn how to wrangle spatial data in R ! Join our workshop on Spatial Data Wrangling with R: A Comprehensive Guide which is a part of our workshops for Ukraine series. 


Here’s some more info: 

Title: Spatial Data Wrangling with R: A Comprehensive Guide

Date: Thursday, April 6th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) 

Speaker: Long Nguyen is a PhD student at SOEP RegioHub at Bielefeld University. He likes to make pretty maps.

Description: This workshop is designed to provide a solid foundation for working with spatial data in R. Starting with fundamental concepts of spatial data types and structures, the workshop provides a systematic overview of techniques for manipulating spatial data, such as spatial aggregation, spatial joins, spatial geometry transformations, and distance calculations. With this focus, the workshop’s aim is to give participants a skill set that is easily extendable and transferable to new data and tools. The data wrangling techniques presented will be accompanied by instructions on creating maps – both static and interactive – to quickly explore and present the results of the operations performed.

Minimal registration fee: 20 euro (or 20 USD or 800 UAH)

How can I register?

  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)
  • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.

How can I sponsor a student?

  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)
  • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.

If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list as only those students who are sponsored can participate). Since the number of sponsored places is usually lower than the number of people signing up for the waitlist, we ask you to sign up via the regular registration process to ensure your participation if you can.

You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.

Looking forward to seeing you during the workshop!


Dataviz with R and ggplot: Using colour and annotations for effective story telling workshop

Learn how to fit use annotations and colors in your ggplot plots! Join our workshop on Dataviz with R and ggplot: Using colour and annotations for effective story telling which is a part of our workshops for Ukraine series. 


Here’s some more info: 

Title: Dataviz with R and ggplot: Using colour and annotations for effective story telling

Date: Thursday, April 20th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone)

Speaker: Cara Thompson, Cara is a freelance data consultant with an academic background, specialising in dataviz and in “enhanced” reproducible outputs. She lives in Edinburgh, Scotland, and is passionate about maximising the impact of other people’s expertise.

Description: If we’re passionate about our data and the patterns we’ve found, a key part of our job is to find effective ways of communicating what we’ve discovered. Intuitive and compelling data visualisations are a great way to draw attention to our main story, and illustrate some of the details. 

In this workshop, we’ll talk about how we can make use of colour, fonts and a few other tricks to make it easier for readers to understand and remember our main story and make our plots publication-ready. We’ll be using R and ggplot to create, modify and annotate the plots we discuss, but the principles apply regardless of the tools you use to plot your data. 

Attendees are encouraged to bring along a plot of their own (which doesn’t need to be made with ggplot!) so that think about how best to apply the principles to their own context – and for a chance for some live feedback during our Q&A session.

Minimal registration fee: 20 euro (or 20 USD or 800 UAH)


How can I register?


  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)
  • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation). You can also submit a plot made by you for a chance for getting feedback!

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.


How can I sponsor a student?

  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)
  • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.

If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).


You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.


Looking forward to seeing you during the workshop!




Structural Equation Modeling in R with the Lavaan package workshop

Learn how to use Structural Equation modeling in R! Join our workshop on Structural Equation Modeling in R with the Lavaan package which is a part of our workshops for Ukraine series. 


Here’s some more info: 


Title: Structural Equation Modeling in R with the Lavaan package


Date: Thursday, March 30th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) 


Speaker: Nino Gugushvili is a post-Doc researcher at the Department of Work and Social Psychology at Maastricht University.


Description: In this workshop, we will go over the basics of structural equation modelling (SEM). We will talk about what SEM is and cover the essential steps of SEM. Next, we will learn path analysis (SEM with observed variables), confirmatory factor analysis, and full SEM (SEM with latent variables + observed variables). Along the way, we will also talk about revising our models and interpreting the results, and we’ll do all this in R, using the Lavaan package.


Minimal registration fee: 20 euro (or 20 USD or 800 UAH)




How can I register?



  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.


How can I sponsor a student?


  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.


If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).



You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.


Looking forward to seeing you during the workshop!





Generalized Additive Models in R workshop

Learn how to fit Generalized Additive Models in R! Join our workshop on Generalized Additive Models in R which is a part of our workshops for Ukraine series. 


Here’s some more info: 


Title: Generalized Additive Models in R


Date: Thursday, April 13th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone)


Speaker: Gavin Simpson, Gavin is a statistical ecologist and freshwater ecologist/palaeoecologist. He has a B.Sc. in Environmental Geography and a Ph.D. in Geography from University College London (UCL), UK. After submitting his Ph.D. thesis in 2001, Gavin worked as an environmental consultant and research scientist in the Department of Geography, UCL, before moving, in 2013, to a research position at the Institute of Environmental Change and Society, University of Regina, Canada. Gavin moved back to Europe in 2021 and is now Assistant Professor of Applied Statistics in the Department of Animal and Veterinary Sciences at Aarhus University, Denmark. Gavin’s research broadly concerns how populations and ecosystems change over time and respond to disturbance, at time scales from minutes and hours, to centuries and millennia. Gavin has developed several R packages, including gratia, analogue, and cocorresp, he helps maintain the vegan package, and can often be found answering R- and GAM-related questions on StackOverflow and CrossValidated.



Description: Generalized Additive Models (GAMs) were introduced as an extension to linear and generalized linear models, where the relationships between the response and covariates are not specified up-front by the analyst but are learned from the data themselves. This learning is achieved by representing the effect of a covariate on the response as a smooth function, rather than following a fixed form (linear, quadratic, etc). GAMs are a large and flexible class of models that are widely used in applied research because of their flexibility and interpretability.

The workshop will explain what a GAM is and how penalized splines and automatic smoothness selection methods work, before focusing on the practical aspects of fitting GAMs to data using the mgcv R package, and will be most useful to people who already have some familiarity with linear and generalized linear models.



Minimal registration fee: 20 euro (or 20 USD or 750 UAH)




How can I register?



  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.


How can I sponsor a student?


  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.


If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).



You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.


Looking forward to seeing you during the workshop!




Using R in an High Performance Computing environment

In a common workflow when programming with R one only deals with a Desktop machine or a Laptop, for instance. This PC environment is convenient for R users as they can focus mainly on coding but it could be the case that the program is taking a long time to run (more than 1 hr. for instance) and one needs many repetitions for the same simulation. In some cases, the program could eat up the available memory of the PC. For a PC environment, tools such as Task Manager (Windows), Activity Monitor (Mac), and top/htop (Linux) could help you to monitor the usage of resources.

High Performance Computing (HPC) centers offer the possibility of increasing the resources (memory/CPU power) your program can utilize. If you opt for moving your workflow to an HPC environment, you would need to learn how to deal with it to take full advantage of the provided resources. In this post, I will write some recommendations that we offer to our users at the High Performance Computing Center North (HPC2N) but that could be applied to other centers as well.

One important aspect, that I observed tends to create issues when moving to HPC, is the terminology. Some of the common terms used in HPC such as cores, CPUs, nodes, shared memory, and distributed memory computing, among others are covered in an R for HPC course that we delivered previously in collaboration with the Parallelldatorcentrum (PDC) in Stockholm.

In an HPC environment, one allocates some resources (cores and memory) for running an R program. In a PC this step is hidden in most cases from the user but under the hood, the R program would assume that all resources in that machine are available and it would try to use them. As in HPC, this step should be done explicitly (through the use of batch text files or some web server such as Open OnDemand) you will need to consciously decide how much CPU and memory power your R program will use in an efficient manner. For instance, if you request 10 cores and 20 GB (RAM) but your application is not parallelized (serial code) and uses < 1GB, 9 cores will be idle during the simulation. Sometimes, it is fine to work with this type of setup if your application needs more memory than what is provided by a single core though. Also, take into account that most HPC centers work in a project-based manner with some possible cost (monetary or with job priority for instance).

Some R packages that make use of Linear Algebra libraries, such as BLAS and LAPACK, can automatically trigger the use of several threads. One way to explicitly control the number of threads to be used is with the package RhpcBLASctl as follows:

library(RhpcBLASctl)
blas_set_num_threads(8) #set the number of threads to 8

In some packages, a parallelization layer has been introduced by using a backend (such as the Parallel package), for instance in heavy routines like bootstrapping (boot package).  Other packages opted for a threaded mechanism, for instance for clustering there is a clusternor package. Examples of the usage of these packages can be found here. 

In the cases already mentioned, someone did the job of parallelizing the application for us and we only need to set the number of threads or workers. If we are the R code developers who want to port some serial into a parallel program, we would need most likely refactor the code and change our programming paradigm. It is important to mention that not all the parts of a program are suitable for parallelization and there could be parts that although parallelizable, one could not observe a significant speedup (ratio of simulation time with 1 core by time with N cores). Thus, one important aspect of code parallelization is to make a code analysis (profiling) by timing parts of the code and locating the bottlenecks that are suitable for parallelization.

In the following code in serial mode (unoptimized one), I am computing the 2D integral of the sinus function between 0 and π in both x and y ranges:

∫∫sin(x+y)dxdy = 0 

integral <- function(N){
# Function for computing a 2D sinus integral
h <- pi/N # Size of grid
mySum <-0 # Camel convention for variables' names

for (i in 1:N) { # Discretization in the x direction
x <- h*(i-0.5) # x coordinate of the grid cell
for (j in 1:N) { # Discretization in the y direction
y <- h*(j-0.5) # y coordinate of the grid cell
mySum <- mySum + sin(x+y) # Computing the integral
}
}

return(mySum*h*h)
}

One way to parallelize this code is by dividing the workload (for loop in the x direction) in an even manner by using some number of workers. In the present case, I will make use of the foreach function that is available in the doParallel package and that allows running tasks in parallel mode. Once I decided what part of the code I will parallelize (x integration) and the tools (foreach), I can refactor my original code. One possible parallel version can be:

integral_parallel <- function(N,i){
# Parallel function for computing a 2D sinus integral
myPartialSum <- 0.0
x <- h*(i-0.5) # x coordinate of the grid cell
for (j in 1:N) { # Discretization in the y direction
y <- h*(j-0.5) # y coordinate of the grid cell
myPartialSum <- myPartialSum + sin(x+y) # Computing the integral
}

return(myPartialSum)
}
 
Notice that here I changed the original programming paradigm because now my function only computes a partial value for each worker. The total value will be known only after all the workers finish their tasks and the result is summarized at the end. The doParallel package requires the initialization of a cluster and the foreach function requires the dopar option to run tasks in parallel mode:

library(doParallel)

cl <- makeCluster(M) # Create the cluster with M workers
registerDoParallel(cl)
r <- foreach(i=1:N, .combine = 'c') %dopar% integral_parallel(N,i)
stopCluster(cl)
integral <- sum(r)*h*h # Summarize and print out final result
integral

The complete example can be found here. 

A common mistake of HPC users is that they try to use batch scripts from other centers, assuming that SLURM or PBS job schedulers behave equally in different centers. Although that is true for the standard features, system administrators at one center could activate switches that are not available or behave slightly differently in other centers.

One recommendation is to use the HPC tools available in your center to monitor the resources’ usage by a simulation. If you have access to the computing nodes the most straightforward way to obtain this information is with top/htop commands. Otherwise, tools such as Grafana or Ganglia would be handy if they are available in your center.

Additional resources:
  • R in HPC course offered by HPC2N/PDC 

The State of Data Literacy 2023, by DataCamp

The State of Data Literacy 2023, by DataCamp
Download Now

In 2023, 87% of leaders recognize data literacy as the most important skill behind basic computer skills. However, only a third of organizations are offering data upskilling.

For most teams, bridging the data literacy skills gap is a universal challenge across modern businesses. Just as workforces adopted computers in the 1980s, and the internet in the 2000s, now organizations must embrace data skills to stay competitive, drive innovation, and attract top talent.

To help close this gap, DataCamp invested months into compelling The State of Data Literacy 2023 report, an expert-led and free-to-download guide to navigating the current data skills revolution, including a foreword from CEO and co-founder, Jonathan Cornelissen.

DataCamp independently surveyed over 550 business leaders across the UK and US to shed light on the most pressing data skills gaps facing modern organizations. In doing so, they uncovered key insights into the strategies data-first organizations are using to upskill their workforces. 

From companies taking their first steps into data literacy to data mature organizations, the report takes multiple leadership perspectives and dives into the business and individual benefits of data upskilling.

A key highlight revealed that leaders who engaged in data upskilling programs experienced more than 70% improvement in quality and speed of decision-making, innovation, customer experience, and employee retention across the board.

Whilst three of the top five fastest-growing skills in the past five years were data skills; business intelligence (41%), data science (37%), and data literacy 30%). In addition, 77% of leaders agreed they would pay a salary premium to candidates with data literacy skills

Download the report now to discover key insights that you can start applying in your organization today.

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RADAR 2023 | Free Annual Summit of the World’s Data Leaders

RADAR 2023 | Free Annual Summit of the World’s Data Leaders

Presented by DataCamp, join a selection of the world’s data leaders for a two-day
digital event designed to help data professionals build stronger careers in 2023.

From gaining a deeper understanding of which skills industry leaders are looking for to navigating the evolving data talent pool, uncover insights on data’s most pressing opportunities through a mix of keynotes, fireside chats, and panels.

Across these expert-led sessions, learn from the people at the forefront of data
transformation with leaders from world-class organizations such as Tableau, Alteryx, Qlik, Salesforce, JetBrains, Google, CBRE, and more.

From R to Python, Jupiter, and beyond, this is an unmissable event for anyone looking to strengthen their wider data skillset and accelerate their careers.

March 22-23 2023, 9 AM – 3 PM EST: Save your seat now.

Key sessions aimed at up-and-coming data scientists:

Breaking Into Data in 2023: How Building a Personal Brand Can Accelerate Data Careers
The secrets to a successful data career with the founder of DATAcated, Kate
Strachnyi. Learn how to build a personal brand, create opportunities through
networking, and build lasting connections within the data community.

How The Data Job Market Is Evolving in 2023
Stay informed on how the data job market is evolving in 2023. Join the CEO of
Orbition Group to learn about breaking into a competitive market, and the
importance of soft skills and value creation in building a successful data career.

An In-depth Guide to the DataCamp Certifications
Ranked at the #1 data certification program by Forbes, DataCamp’s VP of
Certification, Vicky Kennedy, discusses how a DataCamp certification can accelerate your data career. You’ll learn about the two levels of certification and how to prepare for exams. You’ll also uncover insider’s secrets to acing the case study—a take-home exercise based on real-world data scenarios.

Tips For Building An Effective Data Science Portfolio
Portfolio projects are the silver bullet for lack of work experience when it comes to finding data roles. Naledi Hollbruegge, Data Analytics Consultant, and James Le, Developer Advocate at Twelve Labs outline how to effectively present your portfolio projects to highlight your technical and soft skills.

Ask a Hiring Manager: The Keys to Landing a Job in Data Science
Google’s director of Ads Safety, Lukas Tencer, and DataCamp’s Director of Analytics, Jorge Vasquez on what drives successful data applicants. Throughout, they’ll answer audience questions on the key characteristics of successful data applicants, the questions hiring managers expect, and more.

View the full agenda and register here

Working with ChatGPT in R workshop

Learn how to use ChatGPT to improve your coding skills in R! Join our workshop on Working with ChatGPT in R which is a part of our workshops for Ukraine series. 


Here’s some more info: 


Title: Working with ChatGPT in R


Date: Thursday, March 9th, 18:00 – 20:00 CET (Rome, Berlin, Paris timezone) 


Speaker: Dariia Mykhailyshyna, PhD Economics student at the University of Bologna. Previously worked at a Ukrainian think tank Centre of Economic Strategy


Description: In this workshop we will learn how you can fully harness the power of ChatGPT to improve your R coding. We will learn how to access ChatGPT directly from R, how to make it write R code, including fairly long and complicated command, debug its (and your) code, translate code from one coding language to another, comment your code, make it more efficient and more! We will also explore some of the drawbacks of ChatGPT and examine when and why you can’t always rely on it.


Minimal registration fee: 20 euro (or 20 USD or 800 UAH)




How can I register?



  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.


How can I sponsor a student?


  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.


If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).



You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.


Looking forward to seeing you during the workshop!






Survival Analysis with R and Python workshop

Learn more about Survival Analysis and how to apply it both in R and in Python! Join our workshop on Survival Analysis with R and Python which is a part of our workshops for Ukraine series. 
Here’s some more info: 
Title: Survival Analysis with R and Python
Date: Thursday, March 16th, 18:00 – 20:00 CET (Rome, Berlin, Paris timezone) 
Speaker: Christopher Peters is the Principal Data Scientist and ninth employee at Zapier where the mission is to make automation work for everyone. For the last decade, he’s applied survival analysis in R and Python, along with statistics and econometrics to affect positive change for people. He learned many of his skills through self-study with friends as well as during his education at Louisiana State University where he completed his terminal degree, Masters of Applied Statistics. There he was privileged to be advised by reliability analysis giant, Professor Luis A. Escobar. His committee also included co-founder of Penalized B-splines and co-author of The Joys of P-Splines, Professor Brian Marx. As well as Emeritus Professor of Econometrics R. Carter Hill, co-author of Principles of Econometrics. Christopher was recently invited to review the book Statistical Methods for Reliability Data, 2nd Edition, co-authored by Distinguished Professor William Q. Meeker, Professor Luis A. Escobar, and Emeritus Associate Professor Francis G. Pascual. He also recently reviewed Telling Stories with Data by Assistant Professor Rohan Alexander. He loves being in nature and his interests lie in the interactions of technology and nature and span a wide variety of topics related to business, economics and causal inference. You can find him on Twitter at: @statwonk or at http://statwonk.com.
Description: How can we speed up growth? Bring about or prevent important events? Design technology and human processes for high-reliability? Survival Analysis (time-to-event) allows us to wisely answer these questions by allowing us to accurately and precisely allocate credibility among their possible answers. Our interest in future events is insatiable for many serious reasons. Through the benefit of systemization, we can use time-to-event analysis to better understand the possibilities of future events and how they can be reconfigured for the benefit of people and ourselves. Whether it’s causing or preventing important events, or just better understanding them, time-to-event analysis (aka survival or reliability analysis) affords us these abilities through the benefits of systemization. In this two hour workshop, I’ll give a gentle introduction to industrial and commercial application of time-to-event analysis technology in R and Python side-by-side. The workshop will focus on how you can best get started with these technologies and begin to answer these questions yourself on a deeper-level for the purpose of innovation. As part of that, I’ll share what I’ve learned over a decade of applying this high-technology in the SaaS software industry.
Minimal registration fee: 20 euro (or 20 USD or 750 UAH)


How can I register?

  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.
How can I sponsor a student?
  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.


If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).

You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.
Looking forward to seeing you during the workshop!



A Gentle and Applied Introduction to Rcpp workshop

Learn how to use Rcpp package, while contributing to charity! Join our workshop on A Gentle and Applied Introduction to Rcpp to improve your skills which is a part of our workshops for Ukraine series. 
Here’s some more info: 
Title: A Gentle and Applied Introduction to Rcpp
Date: Thursday, February 9th, 18:00 – 20:00 CET (Rome, Berlin, Paris timezone)  
Speaker: Dirk Eddelbuettel is involved with many R packages on CRAN; co-creator of the Rocker Project providing R Docker containers; the Debian/Ubuntu maintainer for R, many CRAN packages, and some other quantitative software; behind several initiatives to make binary packages more easily available ranging from Quantian to the more recent r2u Project; an elected board member of the R Foundation; an adjunct Clinical Professor at the University of Illinois Urbana-Champaign; an editor at the Journal of Statistical Software; and a Principal Software Engineer at TileDB. He holds a MA and PhD in Mathematical Economics from EHESS in France, and a MSc in Industrial Engineering from KIT in Germany.

Description: R has become the lingua franca of statistical research and applications.  It provides an open and extensible system for which the Rcpp package has become the most widely-used package for extending R via native code.  This talk aims to gently introduce going to compiled code without fear thanks to sophisticated tooling R and Rcpp provide which make the otherwise complicated and sometimes feared steps of compiling, linking, loading, and launching compiled code a relative breeze that is accessible directly from R relying on built-in converters to facilitate exchange to and from R for all key data types. The talk will highlight key aspects, and motivations, of using Rcpp—and will also warn of a few common pitfalls. The second half will be centered around a complete worked example of a package using RcppArmadillo that we will build from scratch. Pointers for further study as well as to additional examples will also be provided.
Minimal registration fee: 20 euro (or 20 USD or 750 UAH)


How can I register?

  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.
How can I sponsor a student?
  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

  • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.


If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).

You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.
Looking forward to seeing you during the workshop!