3 courses with the subject DS, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
DS 81082: Applied Data Science for Social Research2
This seminar introduces doctoral scholars to data science methods relevant to social research. The course focuses on predictive and classification algorithms. Students will implement supervised machine learning algorithms such as linear regression (predictive), logistic regression (classification), and k-nearest neighbors (classification), and unsupervised machine learning using k-means clustering (classification). Students will learn the theoretical background of these methods and their application to social science data analysis. The course emphasizes practical implementation and interpretation of results. Students will lear
This seminar introduces students to methods for analyzing qualitative data in social research. The course focuses on practical coding techniques. Students will learn to code qualitative data by keyword to identify themes. Sentiment analysis coding for understanding emotional tones in text will be covered. Basic Natural Language Processing (NLP) concepts, such as Term Frequency-Inverse Document Frequency (TF-IDF), will be introduced to analyze qualitative data. The course emphasizes systematic approaches to qualitative data analysis and interpretation. Students will learn to analyze textual and non-numeric data relevant to soci
This seminar introduces fundamental principles and techniques of data visualization for social research. The course emphasizes the creation of clear and effective visual representations of data. Students will learn to construct simple yet informative visualizations, including histograms for distributions, line charts for trends, scatterplots for relationships, bar charts for comparisons, and pie charts for proportions. The course focuses on best practices for visual design and interpretation within the context of social science data. Students will gain skills to communicate findings and explore patterns through visual means.
