Data Science at Scale

Data analysis is the cornerstone of evidence-based decision making, and this module focuses on scalable data manipulation systems and algorithms. Gain insight into practical systems derived from the frontier of research in computer science and learn to "think" in MapReduce for effective algorithm writing. Explore the landscape of specialized Big Data systems for graphs, arrays, and streams.

Statistical experiment design and analytics are central to data science. This module covers the design of statistical experiments, resampling methods, and a core set of practical machine learning methods and concepts. Additionally, it delves into the common idioms of large-scale graph analytics.

This module emphasizes the importance of effective visualization, ethical considerations around big data, and the use of cloud computing for reproducible data analysis. Gain insight into the state-of-the-art in privacy, ethics, and governance related to big data and data science.

In the Capstone Project, students engage in a real-world project requiring them to apply skills from the entire data science pipeline. Through a collaboration with Coursolve, students work on projects associated with partner stakeholders, gaining practical experience in data science projects.