Learn data science and data management with a variety of courses, workshops and other educational content.
Highlights ⭐
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[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.
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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.
Topics 📋
- Official Statistics
- Data Analysis
- R
- Unstructured Data
- Machine Learning
- Data Processing
- FAIR
- Research Data Management
- Self-Paced
- Data Visualization
- Data Management
- Legal Aspects
- Data Science
- Microsimulation
- Network Data
- Finding Data
- Data Ethics
- Data Literacy
- STATA
- Data Interpretation
- Data Collection
- Data Organization
- Big Data
Self-Paced 💻
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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!
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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!
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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.
Upcoming 🗓️
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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.
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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.
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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.
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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.
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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.
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[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.
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[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.
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[IAB-SMART 3] How to tidy and anonymize raw smartphone geolocation data: Code and Practitioner’s Examples from the IAB-SMART Project
Learn more on how to structure, tidy and anonymize raw geolocation data to create activity indicators using the data collected by the IAB-SMART-App.
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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.
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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.
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The Public Good Statistics: A Reflective Introduction
This self-paced learning module is part of the series “Statistics for the Public Good – Infrastructure Decision Making, Research and Discourse”.
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The Public Good Statistics: Let’s talk about Data Culture!
This workshop is part of the series “Statistics for the Public Good – Infrastructure Decision Making, Research and Discourse”. 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
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Values, Ethics and What They Mean for Data Quality
This workshop is part of the series “Statistics for the Public Good – Infrastructure Decision Making, Research and Discourse”. Various use cases relevant to current policy at international and national level will be used, in which the course participants will act as statistical stakeholders with distributed roles.
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Data 4 Policy: Is the Statistical Era Being Replaced by an Era of Data?
This workshop is part of the series “Statistics for the Public Good – Infrastructure Decision Making, Research and Discourse”. Various use cases relevant to current policy at international and national level will be used, in which the course participants will act as statistical stakeholders with distributed roles.
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Research Data Management for Data Scientists
This online course uses a flipped classroom design, which means that you can watch the weekly hour of video lectures according to your own schedule. In the weekly one-hour online meetings you have the chance to discuss the material and hands-on applications with the instructor and your fellow course participants.
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How to Make Use of Machine Learning & Microsimulation in Official Statistics
This online course uses a flipped classroom design, which means that you can watch the weekly hour of video lectures according to your own schedule. In the weekly one-hour online meetings you have the chance to discuss the material and hands-on applications with the instructors from destatis and Statistics Netherlands.
Any questions? Please contact us BERD Academy.