Digital Humanities in Practice: From Research Questions to Results from edX

From the printing press to the typewriter, there is a long history of scholars adapting to new technologies. In the last forty or fifty years, the most significant advance has been the digitization of books. We now have whole libraries—centuries of history, literature, and philosophy—available instantaneously. This new access is a wonderful benefit, but it can also be overwhelming. If you have hundreds of thousands of books available to you in an instant, where do you even start? With a bit of elementary code, you can study all of these books at once, and derive new sorts of insights.

Computation is changing the very nature of how we do research in the humanities. Tools from data science can help you to explore the record of human culture in ways that just wouldn’t have been possible before. You’re more likely to reach out to others, to work across disciplines, and to assemble teams. Whether you're a student wanting to expand your skillset, a librarian supporting new modes of research, or a journalist who has just received a massive cache of leaked e-mails, this course will show you how to draw insights from thousands of documents at once. You will learn how, with a few simple lines of code, to make use of the metadata—the information about our objects of study—to zero in on what matters most, and visualize your results so that you can understand them at a glance.

In this course, you’ll work on building parts of a search engine, one tailor-made to the needs of academic research. Along the way, you'll learn the fundamentals of text analysis: a set of techniques for manipulating the written word that stand at the core of the digital humanities.

By the end of the course, you will be able to apply what you learn to what interests you most, be it contemporary speeches, journalism, caselaw, and even art objects. This course will analyze pieces of 18th-century literature, showing you how these methods can be applied to philosophical works, religious texts, political and historical records – material from across the spectrum of humanistic inquiry.

Combine your traditional research skills with data science to find answers you never might have expected.

What's inside

Learning objectives

Understand which digital methods are most suitable to meaningfully analyze large databases of text
Identify the resources needed to complete complex digital projects and learn about their possible limitations
Download existing datasets and create new ones by scraping websites and using apis
Enrich metadata and tag text to optimize the results of your analysis

Analyze thousands of books with digital methods such as topic modeling, vector models, and concept search
Test your knowledge by writing and editing code in python, and use these skills to explore new methods of search
By the end of this course, learners will:

Understand which digital methods are most suitable to meaningfully analyze large databases of text
Identify the resources needed to complete complex digital projects and learn about their possible limitations
Download existing datasets and create new ones by scraping websites and using apis
Enrich metadata and tag text to optimize the results of your analysis
Analyze thousands of books with digital methods such as topic modeling, vector models, and concept search
Test your knowledge by writing and editing code in python, and use these skills to explore new methods of search
By the end of this course, learners will:

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores text analysis, which is an essential tool for digital humanities research

Taught by instructors who are recognized for their work in digital humanities

Develops research skills in data science, which is highly relevant to academic research

Provides hands-on experience in building a search engine, which is a valuable skill for researchers

Suitable for learners with a variety of backgrounds, including students, librarians, and journalists

Requires some prior programming experience, which may be a barrier for some learners

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Digital Humanities in Practice: From Research Questions to Results with these activities:

Python Code Exercises

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Enhance your Python skills and prepare for the course by practicing basic coding exercises.

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Set up your Python development environment
Complete a set of online Python tutorials or exercises
Review basic Python syntax and data structures

Read *The Literary Machine*

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Prepare your foundation for the course by understanding how digitization has impacted the study of literature and the humanities.

View Distant Horizons: Digital Evidence and Literary... on Amazon

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Read the introduction and first chapter
Identify the key concepts and arguments presented in the text
Consider how these ideas relate to the course objectives

Text Analysis Techniques Tutorial

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Gain familiarity with text analysis techniques by following a guided tutorial.

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Choose a text analysis tutorial
Follow the steps in the tutorial
Apply the techniques to a small dataset

Five other activities

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Read *The Rise and Fall of the Digital Humanities*

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Explore the history and development of the Digital Humanities to deepen your understanding of the field.

View Guerrilla Theory: Political Concepts, Critical... on Amazon

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Read the book and take notes
Identify the key historical events and figures
Consider the implications for the future of the Digital Humanities

Natural Language Processing Workshop

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Attend a workshop to enhance your skills in natural language processing and text analysis techniques.

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Register for the workshop
Attend the workshop
Apply the techniques learned to your own research

Data Analysis Project

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Strengthen your understanding by applying the course concepts to a real-world data analysis project.

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Define the research question or problem
Gather and prepare the data
Apply appropriate data analysis techniques
Interpret the results
Write a report or present your findings

Course Summary Presentation

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Apply your knowledge by creating a presentation summarizing the key concepts of the course.

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Identify the main themes and ideas from the course
Organize your presentation into a logical structure
Create visual aids to support your presentation
Practice your presentation

Digital Archive Creation Project

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Gain hands-on experience in creating and managing a digital archive of historical materials.

Browse courses on Digital Humanities

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Identify a collection of historical materials
Create a digital repository
Digitize and upload the materials
Create metadata and organize the archive
Provide access to the archive

Career center

Learners who complete Digital Humanities in Practice: From Research Questions to Results will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists study the vast amounts of data generated by modern technology to extract actionable insights. They combine domain expertise with strong quantitative, analytical, and programming abilities. This course helps build a foundation in these areas by teaching basic programming, data analysis, and visualization techniques. Furthermore, it provides hands-on experience with real-world datasets, preparing you for the challenges of working with large and complex data in the field.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, build, and maintain machine learning models to solve real-world problems. This course helps build a foundation in machine learning, data analysis, and programming, which are essential skills for Machine Learning Engineers. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with large and complex data in the field.

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Research Scientist

Research Scientists conduct scientific research to advance knowledge and develop new technologies. This course helps build a foundation in research methods, data analysis, and programming, which are essential skills for Research Scientists. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of conducting research in the field.

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Software Engineer

Software Engineers apply engineering principles to the design, construction, deployment, and maintenance of software systems. This course helps build a strong foundation in programming, data structures, and algorithms, which are essential skills for Software Engineers. Additionally, it provides experience working with real-world datasets and using version control systems, preparing you for the collaborative development environment of software engineering teams.

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Data Analyst

Data Analysts collect, clean, and analyze data to extract actionable insights for businesses. This course helps build a strong foundation in data analysis, statistics, and programming, which are essential skills for Data Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with large and complex data in the field.

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Data Engineer

Data Engineers design, build, and maintain data pipelines to ensure that data is available, reliable, and secure for analysis. This course helps build a strong foundation in data engineering, databases, and programming, which are essential skills for Data Engineers. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with large and complex data in the field.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze data and make predictions in the financial industry. This course helps build a strong foundation in data analysis, statistics, and programming, which are essential skills for Quantitative Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with large and complex financial data.

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Financial Analyst

Financial Analysts provide analysis and recommendations on investments and financial markets. This course helps build a foundation in finance, data analysis, and programming, which are essential skills for Financial Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with financial data in the field.

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Product Manager

Product Managers are responsible for the development and launch of new products and features. This course helps build a foundation in product management, data analysis, and programming, which are essential skills for Product Managers. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of managing products in the field.

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Consultant

Consultants provide advice to businesses on how to improve their performance. This course helps build a foundation in business analysis, data analysis, and programming, which are essential skills for Consultants. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of consulting in the field.

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UX Researcher

UX Researchers study how users interact with products and services to improve the user experience. This course helps build a foundation in research methods, data analysis, and programming, which are essential skills for UX Researchers. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of conducting user research in the field.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems in business and industry. This course helps build a strong foundation in operations research, data analysis, and programming, which are essential skills for Operations Research Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with data in the field.

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Statistician

Statisticians collect, analyze, and interpret data to provide insights for decision-making. This course helps build a strong foundation in statistics, data analysis, and programming, which are essential skills for Statisticians. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with data in the field.

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Business Analyst

Business Analysts analyze business processes and data to identify opportunities for improvement. This course helps build a foundation in business analysis, data analysis, and programming, which are essential skills for Business Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with data in the field.

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Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty in the insurance and financial industries. This course helps build a strong foundation in mathematics, statistics, and programming, which are essential skills for Actuaries. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with data in the field.

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