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Data Science

Hands-on experience to work with actual data sets, teaching students how to filter out data, practice with data analytic tools, and visualize the information.

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What you will learn

Bit University is a non-profit initiative that strives to make data science accessible and available. We develop curriculums and lead lectures at colleges and universities, teaching humanities students how to make the most out of data science tools.

Week1
Week 1

Week 1
Discussion of what data science is and how it applies to the humanities with an overview of the tools that will be taught.
Week1
Week 2

Week 2
Instruction on the basics of Python and how to use the base Python data types and functions as well as best practices in coding.
Week3
Week 3

Week 3
Teaching data manipulation with Pandas such as importing data, cleaning datasets, and filtering and aggregating datasets.
Week4
Week 4

Week 4
Instruction on data visualization using Matplotlib and Pandas with different kinds of graphs and a discussion of best visualization practices.
Week5
Week 5

Week 5
The first practicum which applies the previous lessons to real life datasets. This practicum examines data about the Trans-Atlantic Slave Trade.
Week6
Week 6

Week 6
Teaching advanced data manipulation with Pandas such as different data types in Pandas, column creation and sorting, and data frame joining.
Week7
Week 7

Week 7
Instruction on statistical visualization with Seaborn and Pandas with more control and more options for visuals.
Week8
Week 8

Week 8
Lesson on statistical analysis with NumPy which reviews the motivation behind and basics of statistical analysis in a humanities context.
Week9
Week 9

Week 9
The second practicum analyzes the Freedom on the Move dataset, a real world database of fugitives from North American slavery.
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