2 credit hours

Pick up a recent issue of any business periodical and you are likely to find a testimonial extolling the virtues of business analytics, the practice of applying data and rigorous modeling to derive business insights and drive business planning. Business analytics and its relatives, big data, data mining, business intelligence and predictive analytics represent capabilities that are increasingly sought by firms in a variety of industries.

Data Analytics prepares students to lead analytics-driven organizations in the big data era by giving students advanced machine-learning and data analytics tools. In this course, students are exposed to key methodological tools and concepts through hands-on work with data and software, including:

  • Fundamental data analysis concepts such as data quality and advanced and nonparametric predictive analytics.
  • Machine-learning tools such as neural networks, deep learning, artificial intelligence, clustering, principal component analysis, recommendation analytics, and unstructured data and text analytics.

Students will critically evaluate strategic opportunities and management challenges that arise with data-driven business models through data analyses and discussions in different areas such as retail and financial analytics.

Explore how you can customize your degree by selecting from wide-ranging concentrations of study that focus on specialized disciplines. You can also request information to learn more.

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