Topic models have emerged as a powerful methodological approach in human-centered data science since they lie at the intersection of empirical, positivist and interpretive techniques. Data scientists like topic models because they can provide sophisticated insights about large amounts of text data by incorporating human context and knowledge. This course will provide students with the computational ability to uncover latent topics from text documents and use qualitative, thematic analysis to make sense of them.

This course can be used to fulfil the "Technical" Professional Requirement.