
February 2023
Introduction to Natural Language Processing with R
Course topics will help students add NLP methods to their research & data science toolset. As a technical course with some machine learning elements, limited exposure to programming, and grad-level stats is needed but the vast majority of the content will be focused on applications and examples. Students will learn how to implement a variety of popular text mining methods in R to organize, and process text aimed at identifying insights, extracting frequent terms and assessing sentiment analysis. Learn more…
Find out more »Integrating Memos and Codes in Qualitative Analysis
This course focuses on what it means to develop codes & how to integrate memo writing into the larger process of coding & analysis. Coding and memo writing function as simultaneous & fluid tasks that occur during actively reviewing interviews, focus groups, & multi-media data. We will discuss the tension between deductive & inductive codes & how codes can emerge & shift unexpectedly during analysis. We will also cover how to identify code connections, possible hierarchies, & higher-level themes. Learn…
Find out more »March 2023
Time Series Analysis
This course will be a brief and thorough introduction to modern methods of time series analysis. Topics to be covered include elementary time series models, trend and seasonality, stationary processes, autoregressive/integrated/moving average (ARIMA) processes, fitting ARIMA models, forecasting, spectral analysis, the periodogram, spectral estimation techniques and multivariate time series. Additional topics may be covered if time permits. Learn more and register.
Find out more »Introduction to Constructivist Grounded Theory
This course introduces participants to constructivist grounded theory (CGT). Grounded theory (GT) methods consist of flexible guidelines to fit particular research problems, not to apply mechanically. With these guidelines, you expedite and systematize data collection and analysis. GT methods can assist researchers in making their work more analytic, precise, and compelling. For full course, description, please visit course website. Learn more and register.
Find out more »Cognitive Interviewing
Cognitive interviewing is a methodology researchers use to gain a better understanding of how respondents think when answering specific survey items. This course is designed to provide participants with fundamentals on how to design, conduct, and analyze cognitive interviews. Participants will have the opportunity to practice specific cognitive interviewing techniques, including think-alouds, probing, and observation. Learn more and register.
Find out more »Data Matters: Spring Ahead 2023
Data Matters: Spring Ahead, will feature a selection of our most popular two-day courses. The traditional Data Matters series will return in August 2023. Data Matters gives students the chance to learn about a wide range of topics in data science, analytics, visualization, curation and more from expert instructors. Sponsored by the Odum Institute for Research in Social Science at UNC-Chapel Hill, the National Consortium for Data Science, and RENCI. Learn more and register.
Find out more »Version Control and Collaboration with Git and GitHub
In this two-part (3/21, 3/23) course, participants will learn how to keep track of the code they use in their research using the version control system Git and the collaboration platform GitHub. This course will be a soft pre-requisite for the upcoming “Modular Design and Automated Testing in R” on 4/18 and 4/20. Please visit the course link for information on creating a GitHub account and installing Git prior to the course. Learn more and register.
Find out more »Visual Inquiry in Qualitative Research
Visual imagery has an expanding role in social science research methods. Keeping in mind the needs of a researcher who has little or no formal training in the visual arts, this course will offer criteria for the use of visual methods in qualitative inquiry that will help researchers sharpen their analytical skills. Analyzing images requires an understanding of tacit knowledge: sensory, pre-linguistic embodied empirical evidence. Learn more and register.
Find out more »Version Control and Collaboration with Git and GitHub
In this two-part (3/21, 3/23) course, participants will learn how to keep track of the code they use in their research using the version control system Git and the collaboration platform GitHub. This course will be a soft pre-requisite for the upcoming “Modular Design and Automated Testing in R” on 4/18 and 4/20. Please visit the course link for information on creating a GitHub account and installing Git prior to the course. Learn more and register.
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