Course Detail
Course Components:
This seminar course exposes students to a wide variety of topics in the vast area of data science. These will range from cutting edge research results and open problems to how these techniques transfer to pressing challenges in industry or research labs dependent on these techniques. Data Science, and seminar talks, will include a wide-array of topics in machine learning, data management, data visualization, mathematics of data, data mining, fairness and trustworthiness of algorithms, and algorithmic challenges in big data. Perspectives will include both theoretical developments to challenges to transferring in practice, and all parts in between. The talks will vary significantly in topic, but should mostly be accessible to a graduate student or junior-level undergrad in a data science related area. Students at all levels will get to engage with experts in data science, discover their interests within this space, and explore potential directions and partners for research collaborations.