BS in Data Science

The BS in data science studies the collection, manipulation, storage, retrieval, and computational analysis of data in its various forms, including numeric, textual, image, and video data from small to large volumes. The program combines computer science, information science, mathematics, statistics, and probability theory into an integrated curriculum that prepares students for careers or graduate studies in big data analysis, data science, and data analytics. The course work covers exploratory data analysis, data manipulation in a variety of programming languages, large-scale data storage, predictive analytics, machine learning, data mining, and information visualization and presentation. Data science has emerged as a discipline due to the confluence of two major events: The ability to collect, store, prune, process, and transmit large amounts of data in the cloud. The convergence of programming, statistics, artificial intelligence, and visualization as complementary tools for the analysis and understanding of data. Learning outcomes: Programmatically collect and integrate data from a variety of file, database, and web sources. Programmatically transform data into a form that is fit for analysis. Develop good programming skills and habits in R, Python, Java, C++, HTML, JavaScript, and SQL. Store data in relational and non-relational databases. Design large-scale information storage repositories for “big data” applications. Perform visual and computational analysis of data using statistical and machine-learning methods. Mine text, numeric, and time-series data using automated data mining algorithms. Apply supervised and unsupervised machine learning to complex data analysis tasks. Evaluate machine learning, data mining, and integration algorithms for space and time trade-offs. Publish data and analysis findings via web-based and narrative reports.