Python and Data Processing for the Humanities (RIMA Course)

Faculty:
Course Schedule:
TBD
Professor: TBD
Semester: Spring 2024 (January 29 – May 21)
Subject: CS (Computer Science)
Course Level: 100
Number of Bard Credits: 4
Course Title: Python and data processing for the humanities
Max Enrollment: 22
Schedule: TBD
Distribution Area: Mathematics and Computing
Cross-Listing(s): no
Language of Instruction: English
Automated data analysis is becoming increasingly necessary in the humanities:
Growing amount of data. Data volumes have increased significantly in recent years, including data from social networks, text data, geographic data, etc. In this regard, it is important to learn how to process and analyze large amounts of data in order to benefit from them.
Data integration. The humanities can use data from a variety of sources, such as social media data, surveys, geographic data, and so on. Integrating and analyzing this data can help scientists better understand social, political, and cultural processes.
Requirements for improving efficiency and accuracy. By analyzing data and using the Python programming language, you can improve the accuracy and effectiveness of your research. This can help scientists get more accurate results and save time.
Development of new methods and technologies. The development of data analysis and the use of the Python programming language has led to the creation of new methods and technologies that help scientists work with data more efficiently and accurately.
As a result of completing the course, students will be able to:
- Work with data. Students will learn how to import data, process it, transform and combine data from different sources.
- Perform data analysis. Students will learn data analysis techniques such as frequency analysis, clustering, classification, etc.
- Visualize data. Students will learn the basics of data visualization and learn how to create graphs, charts, and maps to visualize data.
- Work with text data. Students will learn how to analyze and process text data, including thematic modeling, etc.
- Work in the Python programming environment. Students will learn the basics of the Python programming language and its core libraries, such as Pandas, NumPy, and Matplotlib.
- Completing the course will allow students to use Python to analyze data in their research. This will help them improve their research efficiency and accuracy, as well as enable them to process and analyze large amounts of data.