BERD Academy

Learn data science and data management with a variety of courses, workshops and other educational content.

Any questions? Please contact Markus Herklotz BERD Academy.

Registration open

  • Deep Learning with Humans-In-The-Loop: Active Learning for NLP

    The abundance of text data and the advent of powerful deep learning models has led to rapid advancements in Natural Language Processing. However, adapting models to specialized tasks still requires a nuanced understanding of the data. Join this hands-on workshop to dive into Active Learning!

    With Lukas Rauch
    Kassel, July 4th 2024

Self-Paced 💻

  • Data Science with Python

    You want to learn Python for Data Science, but don’t find the time to visit synchronous courses regularly? Register for this self-paced course and learn all you need to start with Python on your own schedule!

    With Nicolas Heist and Sven Hertling
  • Data Science with R

    You want to learn R for Data Science, but don’t find the time to visit synchronous courses regularly? Register for this self-paced course and learn all you need to start with R on your own schedule!

    With Leonie Gehrmann
  • Introduction to Machine Learning (I2ML) 🔗

    Dive into Machine Learning (ML) on your own pace. This extensive online course from LMU Munich experts starts with the basics and guides you to the more advanced components of Machine Learning.

All upcoming 🗓️

  • Workshop-Reihe Forschungsdatenmanagement in der Fachreferatsarbeit (Wirtschafts- und Sozialwissenschaften) 🔗

    Das Thema Forschungsdatenmanagement (FDM) gewinnt immer mehr an Bedeutung als forschungsnaher Dienst von Bibliotheken. Dabei können Fachreferent*innen eine entscheidende Rolle insbesondere bei der fachspezifischen Beratung Forschender spielen.

    BERD@NFDI möchte mit dieser Fortbildungsreihe im Rahmen seiner BERD Academy einen Einstieg in verschiedene Aspekte des FDM bieten und so einen Beitrag zur Integration der FDM-Beratung die Fachreferatsarbeit der Wirtschafts- und Sozialwissenschaften leisten.

    Die Fortbildung besteht aus sechs 90-minütigen online Workshops, jeweils montags ab dem 08.04.2024. Es werden keine Vorkenntnisse vorausgesetzt. Die Teilnahme ist kostenlos. Pro Termin ist die Zahl der teilnehmenden Personen auf 16 begrenzt.

    With Anja Perry, Irene Schumm, Jan Kamlah, Jorge Murcia Serra, Renat Shigapov, and Vasilka Stoilova
    Online, April 8th to May 13th 2024
  • Deep Learning with Humans-In-The-Loop: Active Learning for NLP

    The abundance of text data and the advent of powerful deep learning models has led to rapid advancements in Natural Language Processing. However, adapting models to specialized tasks still requires a nuanced understanding of the data. Join this hands-on workshop to dive into Active Learning!

    With Lukas Rauch
    Kassel, July 4th 2024
  • Turning PDFs into Research Data

    Do you ever feel that the data you need for your research is accessible but it’s not in a convenient table? Join this online course to learn how to scrape data from PDFs and make it usable by using OCR and NLP!

    With Jack Collins
    Online, Starting Aug 27, 2024
  • Make your research reproducible – a hands-on course (2024)

    In this online course, we will get your research project organized, under version control, stable, and published so that you can confidently say that your research is reproducible.

    With Heidi Seibold
    Online, Starting Sep 25, 2024
  • Data Science with Telecommunication Data

    Do you work with telecommunication data or are interested in flow and mobility data to adress applied research questions from sociology, economics or related fields? Join this workshop in Munich!

    With Göran Kauermann
    Munich, Autumn 2024


Past Events

  • DataFest 2024 🔗

    Join DataFest Germany, an 48-hour data competition held annually in Mannheim and Munich, where teams of students dive into a mystery dataset to uncover insights and create impactful analyses. Supported by experts from academia and industry, you have the chance to showcase your work to renowned data professionals and win prizes while networking with potential employers at the CareerFair.

    Mannheim, April 5th to 7th 2024
  • AI based Methods for Using Text as Data in the Social Sciences

    Join this workshop in Leipzig to get to know state of the art AI applications to use text as data for social science research.

    With Christian Kahmann, Christopher Schröder, Erik Körner, Felix Helfer, Gerhard Heyer, and Thomas Eckart
    Leipzig, December 12th 2023
  • Microsimulation & Machine Learning with Official Statistics Data

    This online course provides an overview of Big Data, machine learning, & microsimulations; and its application to official statistics data. You will watch the online videos & do the assignments on your own pace and meet weekly with the course instructors.

    With Hanna Brenzel, Hariolf Merkle, Marco Puts, and Piet Daas
    Online, Meetings: Nov 2, Nov 9, Nov 23, Nov 30
  • Data Literacy Essentials: Collecting Research Data 🔗

    How do I collect research data? What is the difference between qualitative and quantitative data? We will give you an overviewof the many ways in which research data can be obtained. Examples are given of the differences between various data sources and the theoretical and practical aspects that need to be taken into account in order to obtain the appropriate data for the research project.

    With Markus Herklotz November 2nd 2023
  • Data Literacy Essentials: Organizing Research Data 🔗

    How do I store research data correctly? How do I document research data? What does data security mean? In this introduction we will cover among other topics naming conventions as well as different storage locations and their advantages and disadvantages. So one thing is for sure: data loss was yesterday.

    With Irene Schumm Online, October 26th 2023
  • Data Literacy Essentials: Searching Research Data 🔗

    How do I find research data? And how do I get access to the important databases for my own field? We will give you a short introduction in which we will also show you how to identify usable data and how to cite it correctly.

    With Larissa Will Online, October 19th 2023
  • Make your Research Reproducible – A Hands-On Course

    In this online course, we will get your research project organized, under version control, stable, and published so that you can confidently say that your research is reproducible.

    With Heidi Seibold
    Online, Meetings: Oct 17, Oct 24, Nov 7, Nov 14
  • Data 4 Policy: Is the Statistical Era Being Replaced by an Era of Data?

    In this workshop, we will discuss the differences between data driven and question driven approaches. We will explore the relationship of data, facts, and policy. Let’s discuss the future of data and society!

    With Walter J. Radermacher
    Munich, October 12th, 2023 (9-12, 14-17)
  • Values, Ethics and What They Mean for Data Quality

    In this workshop, you will gain a basic understanding of why ethics and values play such an important role when using data. You will get to know different ethical principles and discuss if they are still up-to-date to current developments and new data sources.

    With Walter J. Radermacher
    Munich, October 11th, 2023 (9-12, 14-17)
  • The Public Good Statistics: Let’s talk about Data Culture!

    In this workshop, you will gain a basic understanding of data literacy and data culture, not only for data professionals but for all types of users of data and statistics.

    With Walter J. Radermacher
    Munich, October 10th, 2023 (9-12, 14-17)
  • Data Literacy Essentials: Understanding Research Data 🔗

    How do I evaluate data quality for research data? What is a „good“ research question? In this short introduction we will outline ways to improve the quality of your reseach.

    With David Philip Morgan Online, October 5th 2023
  • Data Literacy Essentials: Crash Course Data Literacy 🔗

    What is data literacy? We will provide a brief introduction to data literacy and show you how a planful approach to research data can contribute both to successful university studies and scientific research.

    With Irene Schumm Online, September 28th 2023
  • StatTag and StatWrap for Conducting Collaborative Reproducible Research

    This talk will describe two software tools designed to address the challenges of collaborative, reproducible research: StatTag and StatWrap.

    With Leah J Welty
    Online, Sep 28 2023, 10.15am – 11.15am CEST
  • DSSGx Lecture: Analyzing Open-ended (Audio) Survey Responses: Insights from a research project

    Join online sessions from the Data Science for Social Good (DSSG) lecture series for free!

    With Paul Bauer
    Online, September 21th 2023, 3:00pm – 4:00pm CEST
  • DSSGx Lecture: Open Science @ MCML

    Join online sessions from the Data Science for Social Good (DSSG) lecture series for free!

    With Moritz Herrmann
    Online, September 14th 2023, 3:00pm – 4:00pm CEST
  • DSSGx Lecture: Responsible AI to Benefit Society

    Join online sessions from the Data Science for Social Good (DSSG) lecture series for free!

    With Kit Rodolfa
    August 31th 2023, 5:00pm – 6:00pm CEST
  • DSSGx Lecture: Democratizing our Data

    Join online sessions from the Data Science for Social Good (DSSG) lecture series for free!

    With Julia Lane
    Online, August 24th 2023, 3:00pm – 4:00pm CEST
  • DSSGx Lecture: DSSG Berlin

    Join online sessions from the Data Science for Social Good (DSSG) lecture series for free!

    With Hasan Shaukat
    Online, August 17th 2023, 3:00pm – 4:00pm CEST
  • Data Science for Social Good

    Hosted by the Chair of Frauke Kreuter and the Munich Center for Machine Learning (MCML), this 2-month full-time program joins forces of aspiring talents in the area of Data Science in small groups to work on projects with a positive societal impact.

    Munich, August – September, 2023
  • A Connected World: Data Analysis for Real-World Network Data

    This workshop provides you with an overview of different research strains in the field of network data analysis. In a hands-on session, you will learn to analyze a real-world network dataset through the use of existing, readily available software packages.

    With Cornelius Fritz, Giacomo De Nicola, and Göran Kauermann
    Munich, July 19th 2023
  • [IAB-SMART 3] How to tidy and anonymize raw smartphone geolocation data: Code and Practitioner’s Examples from the IAB-SMART Project

    Learn how to structure, tidy and anonymize raw geolocation data to create activity indicators using the data collected by the IAB-SMART-App.

    With Andreas Filser
    Online, July 12th 2023, 1:00pm – 2:00pm CEST
  • [IAB-SMART 2] What do geolocation smartphone data add to a survey panel? –  Available indicators from the IAB-SMART Project

    In this webinar, you will get to know the new IAB-SMART data module with activity indicators from smartphone sensor data.

    With Florian Zimmermann
    Online, July 5th 2023, 1:00pm – 2:00pm CEST
  • [IAB-SMART 1] The IAB-SMART Study: Collecting Behavioral Smartphone Sensor Data for Social Research

    In this webinar, you will get an overview on how to collect smartphone data ethically and transparently with an Android app.

    With Georg-Christoph Haas
    Online, June 28th 2023, 12pm noon – 1:30pm CEST
  • Women in Data Science (WiDS) Munich 🔗

    Women in Data Science (WiDS) elevates women in the field by providing inspiration, education, community, and support. Join the regional WiDS event in Munich to get to know outstanding women doing outstanding work in Data Science.

    Munich, June 19th 2023
  • FAIR Data Week: R for Reusable 🔗

    Findable, Accessible, Interoperable, and Reusable. These are the principles of FAIR Data and they have become a standard for good practice in research data management. In this 20 minute talk, we will cover how the reusability of your data can be achieved and why it can be beneficial for you to improve the reusability of your data.

    With Renat Shigapov
    Online, June 2nd 2023
  • FAIR Data Week: I for Interoperable 🔗

    Findable, Accessible, Interoperable, and Re-usable. These are the principles of FAIR Data and they have become a standard for good practice in research data management. In this 20 minute talk we will cover how the interoperability of your data can be achieved and why it can be beneficial for you to improve the interoperability of your data.

    With Renat Shigapov
    Online, June 1st 2023
  • FAIR Data Week: A for Accessible 🔗

    Findable, Accessible, Interoperable, and Re-usable. These are the principles of FAIR Data and they have become a standard for good practice in research data management. In this 20 minute talk we will cover how the accessibiliy of your data can be achieved and why it can be beneficial for you to improve the accessibiliy of your data.

    With Renat Shigapov
    Online, May 31st 2023
  • FAIR Data Week: F for Findable 🔗

    Findable, Accessible, Interoperable, and Re-usable. These are the principles of FAIR Data and they have become a standard for good practice in research data management. In this 20 minute talk we will cover how the findability of your data can be achieved and why it can be beneficial for you to improve the findability of your data.

    With Renat Shigapov
    Online, May 30th 2023
  • DataFEST Germany 2023 🔗

    Are you a student from the social sciences, computer science or data science? Register your team now for DataFEST, where you will work with a large, not-publicly-available, real-world dataset for a weekend. Tutorials, workshops, mentors and professional consultants are available for support.

    Munich, April 14th to 16th 2023
  • Data Literacy Essentials: Processing Data (R) 🔗

    In this session we will introduce you to R, a programming language that allows you to edit, visualize and analyze data. We will give you an introduction to the programming environment RStudio, teach you the basics of syntax and show you examples of the possibilities that open up with the use of R. No previous knowledge is assumed.

    With David Morgan
    Online, March 30th 2023
  • Data Literacy Essentials: Processing Data (STATA) 🔗

    In this session we will introduce you to Stata, a widely used statistical program that allows you to process, visualize and analyze data. We will give you an introduction to the most important functions and the basics of operation and use examples to show you the possibilities that open up when using Stata. No previous knowledge is assumed.

    With Hendrik Platte-Burkhardt
    Mannheim or online, March 23rd 2023
  • Data Literacy Essentials: Visualize Data 🔗

    How do you visualize research data? Let’s face it: depending on the extent, research data can literally „overwhelm“ you at first glance. So how do you manage to present your data in an appealing way so that other people can also get a quick overview? We show you how to present data graphically.

    With Richard Traunmüller
    Online, March 16th 2023
  • Data Literacy Essentials: Data Ethics Basics 🔗

    Which ethical requirements must be observed when handling data? What are the ethical obligations for researchers along the data lifecycle? We will find answers to these questions and delve into the basics of data ethics in this Data Literacy Essential.

    With Vasilka Stoilova
    Online, March 9th 2023
  • Machine Learning Bootcamp in R (€) 🔗

    Dive deep into Machine Learning with R in these webinar offered by Essential Data Science Training.

    Online, March 6th to 10th 2023
  • Data Literacy Essentials: Analyze Data 🔗

    How to analyze research data? In this introduction, we will show you the first steps you can take to analyze your research data and will give you an overview of the most important methods of descriptive and inferential statistics.

    With Hendrik Platte-Burkhardt
    Online, March 2nd 2023
  • Data Analysis Bootcamp in R (€) 🔗

    Dive deep into Data Analysis with R in these webinars offered by Essential Data Science Training.

    Online, February 27th to March 2nd 2023
  • A Connected World: Data Analysis for Real-World Network Data

    This workshop intends to provide interested scholars with an overview of different research strains in the field of network data analysis. In particular, we will work with data relating to international political interactions, such as the international trade of weapons, migration, and conflicts but also with classical social network data. Participants will be introduced to the analysis of network data from both a substantive and statistical perspective. In a hands-on session you will learn to analyze a real-world network dataset through the use of existing, readily available software packages.

    With Cornelius Fritz, Giacomo De Nicola, and Göran Kauermann
    Munich, December 8th 2022
  • Focused Tutorial on Capturing, Enriching, Disseminating Research Data Objects

    This Focused Tutorial will provide knowledge, methodological and technical expertise in the areas of data, metadata, taxonomies and standards with a view to the FAIR principles, and promotes a cross-disciplinary exchange and networking between the participating consortia.

    With Canan Hastik, Jan Kamlah, Renat Shigapov, and Thomas Schmitt
    Mannheim or online, November 24th to 25th 2022
  • Big Data Analyses and New Developments in Research Data Centres (RDC) 🔗

    Das Ziel des Workshops besteht darin, Forschenden der Ökonomie die Möglichkeit zu geben, sich zu neuen Datentypen und Entwicklungen der Datennutzung auszutauschen. Das umfasst folgende Aspekte:
    – Big-Data-Analysen: Nutzung unstrukturierter Daten – aus: Internet (Stichwort: Webscraping), soziale Medien, Messdaten u. a. große Datenmengen – durch Umwandlung in strukturierte Forschungsdaten
    – Generierung von Forschungsdaten durch Verknüpfungen von administrativen und/oder Befragungsdaten, z. B. via Algorithmen maschinellen Lernens
    – Innovative Datenzugangswege in FDZ: z. B. FDZ-in-FDZ, Remote Access, Cloud

    With Sandra Gottschalk and Uli Krieger
    Mannheim, November 24th to 25th 2022
  • GDPR applicability – introduction to the interactive Virtual Assistant iVA

    In this follow-up Data Literacy Snack we will tackle the question “When is GDPR applicable?”. Along with some practical examples we will introduce the interactive Virtual Assistant iVA: a tool, which helps researchers deal with data protection topics.

    With Markus Herklotz and Vasilka Stoilova
    Online, November 23rd 2022
  • How to Make Use of Machine Learning & Microsimulation in Official Statistics

    This course gives an overview of advanced topics in official statistics such as Big Data, machine learning, and microsimulations. The benefits and downsides of using Big Data as a data source for official statistics production are discussed and examples of its use are given, including machine learning applications.

    With Hanna Brenzel, Hariolf Merkle, Marco Puts, and Piet Daas
    Online, November 14th to December 5th 2022
  • Data Protection Basics

    In this Data Literacy Snack we will delve into the basics of privacy and data protection laws while focusing on the ever so relevant General Data Protection Regulation (GDPR).

    With Vasilka Stoilova
    Online, November 9th 2022
  • Data Literacy Essentials: Daten organisieren 🔗

    Wie organisiert man Forschungsdaten? In dieser Einführung zeigen wir Ihnen, wie Sie Ihre Forschungsdaten organisieren und sichern. Dabei gehen wir sowohl auf Namenskonventionen als auch auf unterschiedliche Speicherorte sowie deren Vor- und Nachteile ein. So ist eines sicher: Datenverlust war gestern.

    With Irene Schumm and Lorena Steeb
    Online, October 27th 2022
  • Data Literacy Essentials: Daten erheben 🔗

    In der Einheit “Daten erheben” wird ein Überblick darüber gegeben, auf welche vielfältige Weise Daten gewonnen werden können. Dabei wird beispielhaft gezeigt, wodurch sich verschiedene Datenquellen unterscheiden und welche theoretischen sowie praktischen Aspekte zu beachten sind, um die für das Forschungsvorhaben passenden Daten zu gewinnen.

    With Markus Herklotz
    Online, October 20th 2022
  • Data 4 Policy: Is the Statistical Era Being Replaced by an Era of Data?

    In this respect it is about more than just the application of statistical methods. Rather, the focus must be on the questions that a society wants to have answered with solid statistics for its current, pressing and conflict-laden issues. Other aspects then play a role here, namely whether politics values and finances this infrastructure, whether corresponding data literacy is available in the population at large, and so on.

    With Walter Radermacher
    Munich, October 13th 2022
  • Data Literacy Essentials: Daten verstehen 🔗

    Wie identifiziert man eigentlich die Qualität und Verwerndbarkeit von Forschungsdaten? Wir geben eine kurze Einführung. Hierbei zeigen wir, wie Sie “gute” Daten erkennen können und welche Kriterien hierfür wichtig sind.

    With Canan Hastik
    Online, October 13th 2022
  • Values, Ethics and What They Mean for Data Quality

    New data sources and data science methods open up substantial opportunities for research and for improving statistics. However, the integration of traditional and newer methods requires more than the merging of methodology and technology. Rather, it is also a matter of further developing the other dimensions of good information quality, namely those of infrastructure, language and values, simultaneously in an integrative manner in this sense.

    With Walter Radermacher
    Munich, October 12th 2022
  • Should Government Data Concern or Serve us?

    This workshop will provide a discussion of the five safes framework in helping conceptualize and implement the joint determination of risk and utility. It will describe the Coleridge Initiative’s use of the US FedRAMP framework, as well as the FedRAMP approach in more detail, in terms of minimizing risk. It will then work through the role of training classes in creating value.

    With Julia Lane
    Munich, October 11th 2022
  • Data Literacy Essentials: Daten recherchieren 🔗

    Wie findet man Forschungsdaten? Und wie erhält man Zugang zu den wichtigen Datenbanken für das eigene Fachgebiet? Wir geben Ihnen eine kurze Einführung. Hierbei zeigen wir Ihnen außerdem, wie Sie nutzbare Daten identifizieren und richtig zitieren können.

    With Lorena Steeb
    Online, October 6th 2022
  • The Public Good Statistics: Let’s Talk About Data Culture!

    You will get to know the conditions for evidence-based policy to contribute to shaping the transformation processes that arise in times of crisis and to reducing social conflicts to their minimum. In addition to its function as a common language for public (national and international) discourse, public statistics also serve as a data source and partner for research on individual and social behavior.

    With Walter Radermacher
    Munich, October 1st to 9th 2022
  • Statistics for the Public Good – Infrastructures for Decision Making, Research, and Discourse Workshop SeriesStatistics for the Public Good

    In this workshop series, you will learn about the DNA of official statistics, what quality means and how to achieve it, especially under the challenges of modern societies. Various use cases relevant to current policy at the national and international level will be used, in which the course participants will act as statistical stakeholders with … Continue reading Statistics for the Public Good – Infrastructures for Decision Making, Research, and Discourse Workshop SeriesStatistics for the Public Good

    With Walter J. Radermacher
    Munich, October 1st to 13th 2022
  • Democratizing Data: AI tools for discovery

    In this workshop we will not just present the results, but have hands-on tutorials to work with the resulting API, dashboard, Jupyter Notebooks and visualization tools. The goal is to inspire BERD researchers to collaborate – or to develop new approaches to building an Amazon.com for European scientific and public data.

    With Julia Lane
    Mannheim, September 29th 2022
  • Data Literacy Essentials: Crash Course Data Literacy 🔗

    Was ist Datenkompetenz eigentlich genau? Wir geben eine kurze Einführung in das Thema Data Literacy und zeigen, wie ein planvoller Umgang mit Daten zu einem erfolgreichen Studium beitragen kann.

    With Irene Schumm
    Online, September 29th 2022
  • Data Science with R

    You want to learn R for Data Science, but don’t find the time to visit synchronous courses regularly? Register for this self-paced course and learn all you need to start with R on your own schedule!

    With Leonie Gehrmann
    Online, self-paced
  • Introduction to Machine Learning 🔗

    This website offers an open and free introductory course on (supervised) machine learning. The course is constructed as self-contained as possible, and enables self-study through lecture videos, PDF slides, cheatsheets, quizzes, exercises (with solutions), and notebooks.

    With Bernd Bischl, Daniel Schalk, Fabian Scheipl, Lisa Wimmer, Ludwig Bothmann, and Tobias Pielok
    Online, self-paced
  • Data Science with Python

    You want to learn Python for Data Science, but don’t find the time to visit synchronous courses regularly? Register for this self-paced course and learn all you need to start with Python on your own schedule!

    With Nicolas Heist and Sven Hertling
    Online, self-paced
  • Introduction to Machine Learning (I2ML) 🔗

    Dive into Machine Learning (ML) on your own pace. This extensive online course from LMU Munich experts starts with the basics and guides you to the more advanced components of Machine Learning.

    Online,