Data Science Summer School

A series of one-day workshops on data science methods and applications

The World is one big data problem

Acquire the tools and mindset to solve it this summer!

The Data Science Summer School is a series of theoretical and practical workshops on the exciting methods and technologies currently employed by industry, government, and civil society to address the world's most complex problems. Data Science Summer School will provide the following benefits for participants:

  • Single day (4-hour) workshops covering theory and application;
  • Instruction from professors, researchers, and industry experts;
  • Networking opportunities with other Summer School participants;
  • Certificate of Attendance for participation in the Summer School;
  • And best of all, attendance is fully sponsored;

The Data Science Summer School is organized by the Hertie School Data Science Lab with the support of the SCRIPTS Cluster of Excellence and the Stifterverband für die Deutsche Wissenschaft.

Partner Institutions



Courses

The summer school courses will be held virtually on Zoom Webinar

Introduction to R Programming

Learn how to use and be comfortable with the statistical programming language R


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Text as Data: quantitative text analysis with R

Understand the fundamentals of quantitative text analysis using statistical procedures


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Modern Survey Methods

Explore the latest development in the science of modern survey methodologies


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Data Visualization with R

Have fun with data visualization - one of the most powerful tools to explore, understand and communicate patterns in quantitative information.


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Introduction to Programming with Python

Learn the basics of computer science with one of the most popular programming language. Topics include data types, control structures, functions, and an introduction to the principles of object-oriented programming and computational complexity.


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Image as Data: quantitative image analysis with R and Python

Statistical basis and implementation of two methods for the unsupervised and supervised analysis of images: a visual structural topic model based on the Bag of Visual Words, and Convolutional Neural Networks (CNNs).


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Data Access: Web Scraping with R

This short course teaches students how to extract, store, and process data from the Internet using the R statistical programming language.


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Research Design and Causal Analysis with R

Study the basic strategies of research design, including observing control variables, issues surrounding the analysis of causal mechanism, as well as instrumental variable approaches.


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Natural Language Processing: Text classification

A short guide on how to understand and implement automated classification of text into categories.


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Natural Language Processing: Topic Modeling

Investigate the process of how to extract abstract topics from a collection of data and documents.


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Network Analysis (Social Network Analysis)

Acquire the knowledge on how to analyze social network by investigating social structures through the use of networks and graph theory.


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Experimental Designs and Experimental Methodology

Explore and exploit the toolkit and design of experiments for your research


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Social-media based experiments

Experiment with ideas. Test and see which works better. Analyze your data.


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Introduction to Machine Learning

An exciting introduction into how to investigate data through the lens of machine learning algorithms.


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Introduction to Deep Learning

A brief foray into the powerful deep learning methods and applications for extracting insights from unstructured data.


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GeoData and Spatial Data Analysis with R

The workshop will introduce the R package sf for handling spatial data in tables, and operating on them using spatial measures, predicates and transformers.


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Contact Us

Location:

Data Science Lab, Hertie School
Friedrichstraße 180, Berlin

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