Digital Humanities: From Research to Results
Learn to combine literary research with data science in this Harvard course on digital humanities practices.
Course Cost
₹ 18,587
Intermediate
Skill Level
10 Weeks
Self-paced Video lessons
This course explores the intersection of humanities research and data science, focusing on how computational methods can enhance the study of literature, history, and philosophy. Participants will learn to use basic coding tools to analyze large digital document collections, deriving insights that were previously impossible. The curriculum covers text analysis techniques, metadata manipulation, and visualization methods, all applied to real-world humanities research questions. Students will build parts of a search engine tailored for academic research, learning fundamental text analysis skills applicable to various fields. The course emphasizes practical skills, including downloading datasets, web scraping, using APIs, and writing Python code. By the end, learners will be able to apply these digital methods to diverse materials, from 18th-century literature to contemporary speeches, journalism, and even art objects.

3.9
5,556 Enrolled

English
What you'll learn
Understand which digital methods are suitable for analyzing large text databases
Identify resources and limitations for complex digital humanities projects
Download datasets and create new ones using web scraping and APIs
Enrich metadata and tag text to optimize analysis results
Apply digital methods like topic modeling and vector models to analyze thousands of books
Write and edit Python code for text analysis and search optimization
Visualize results of computational analyses for humanities research
Interpret and contextualize findings from digital methods within humanities scholarship
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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Module Description
This course provides a comprehensive introduction to digital humanities methods, focusing on the practical application of data science techniques to humanities research. The curriculum covers a range of topics, including text analysis, metadata manipulation, web scraping, and data visualization. Students will learn to use Python for humanities research, building skills in coding and data manipulation. The course emphasizes hands-on learning, with projects that include building parts of a search engine and analyzing large text corpora. Participants will explore advanced concepts such as topic modeling and vector models, applying these techniques to real-world humanities datasets. Throughout the course, students will learn to identify appropriate digital methods for different research questions, understand the limitations and potential of these methods, and interpret the results of computational analyses in the context of humanities scholarship.
Fee Structure
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Faculties
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Frequently asked Questions
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