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Data Science: Visualization and Analytics in R - Period 2
Computer Science Program
Amsterdam, Netherlands
Dates: 8/20/22 - 12/24/22
Data Science: Visualization and Analytics in R - Period 2
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Humanities
Instruction in: English
Course Code: S_DSVAR
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 84
DESCRIPTION
The explosion of digital information and increasing efforts to digitize existing information sources has produced a deluge of data, such as digitized historical news archives, literature, policy and legal documents, political debates and millions of social media messages by politicians, journalists, and citizens. Graphs and charts let you explore and learn about the structure of the information you have collected. Good data visualizations enable you to communicate your ideas and findings.
This course will offer analytical and practical training in digital visualization techniques using the open-source platform R. This course is placed in the broader scope of Digital Humanities and Social Analytics. In terms of critical reflection and skills this is a more advanced course within the Minor Digital Humanities and Social Analytics. An important part of the classes will entail practical training in the visualization of data: what are the "right numbers" to present, how to present uncertainty in data, which ties in a network are important enough? The course will teach you how to transform data to a visual: from a basic graphical display to animated and BBC-worthy graphics (e.g. see https://www.r-bloggers.com/create-data-visualizations-like-bbc-news-with
This course invites you to develop visuals from many data sources, such as textual data, networked data, etc. At the end of the course you will be able to use attractive visualizations to present your research results in both oral and written communications.
Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
This course will offer analytical and practical training in digital visualization techniques using the open-source platform R. This course is placed in the broader scope of Digital Humanities and Social Analytics. In terms of critical reflection and skills this is a more advanced course within the Minor Digital Humanities and Social Analytics. An important part of the classes will entail practical training in the visualization of data: what are the "right numbers" to present, how to present uncertainty in data, which ties in a network are important enough? The course will teach you how to transform data to a visual: from a basic graphical display to animated and BBC-worthy graphics (e.g. see https://www.r-bloggers.com/create-data-visualizations-like-bbc-news-with
This course invites you to develop visuals from many data sources, such as textual data, networked data, etc. At the end of the course you will be able to use attractive visualizations to present your research results in both oral and written communications.
Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.