Where to continue?
Here I'll gather some relevant links to further resources. I think these are good, but they're also somewhat of a random selection.
Term glossaries:
Tools and data processing:
The programming humanist:
Python Programming for the Humanities, the best introduction to programming for humanists that I could find
The programming historian, lessons and tutorials for doing various DH things
Eloquent Javascript, a nicely built general, interactive introduction to programming
On visualisation:
Fundamentals of Data Visualization (a good introductory book on choosing suitable visualisations for highlighting different aspects in data, and avoiding pitfalls in tuning them)
Data Visualization - a practical introduction (starts with a good chapter organised around general principles, but then continues with very down to earth practical instructions on how to plot stuff using ggplot2 in R. This is very useful, but doesn't cover the general view on different graph types and their usefulness. Thus, a very nice complement to the book before)
On statistics and computational data science:
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse!, a very good and clear resource introducing both statistical concepts, as well as how to apply them in practice in R and Tidyverse. An excellent follow-up to the introduction in this course.
Online Statistics Education: An Interactive Multimedia Course of Study, an excellent alternative simple introduction to core statistical concepts
Introduction to Open Data Science MOOC at the University of Helsinki
Computational and Inferential Thinking - The Foundations of Data Science, an excellent introduction to statistical analysis with interactive Python notebooks
R for Data Science book
The historian’s macroscope, a good general-purpose book introducing different types of humanities data analysis
Further resources to go through that may cover bits and bobs missed by the above:
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