Advanced Data Analytics

Catalog description

It provides applied programming experience with hands-on projects involving real data. It explores and uses popular data analysis platforms and tools. Completion of the course will be primarily assessed with graded practice exercises showing the student's ability to: (1) Apply command-line and pattern-matching techniques to automate data preparation and transformation tasks; (2) Analyze datasets using vectorized computation, statistical methods, and exploratory data visualization; (3) Acquire, parse, and integrate data from heterogeneous and semi-structured data sources; (4)Design and implement interactive, data-driven web artifacts to communicate analytical results; (5) Apply data mining techniques such as for clustering, classification, and dimensionality reduction to extract meaningful patterns from data; (6) Implement scalable data analysis workflows and evaluate their performance on large datasets.