Course Detail

This course covers tools and techniques used in applying statistical and machine learning approaches to large, real-world data sets. Through hands-on assignments and projects, students learn popular programming models and toolkits for performing large-scale data analyses. The course also explores distributed and high-performance frameworks that can be used in data-intensive applications for filtering, clustering, and classifying data. Advanced analytic approaches discussed include data sketching, principal component analysis, recommendation algorithms, topic modeling, Bayesian networks, and deep learning. Spring - even years.