Data Science

Unique Features

Program Objectives

• Collect data from numerous sources (databases, files, XML, JSON, CSV, and Web APIs) and integrate them into a form in which the data is fit for analysis.
• Use R and Python to explore data, produce summary statistics, and perform statistical analyses; use standard data mining and machine-learning models for effective analysis.
• Select, plan, and implement storage, search, and retrieval components of large-scale structure and unstructured repositories.
• Retrieve data for analysis, which requires knowledge of standard retrieval mechanisms such as SQL and XPath, but also retrieval of unstructured information such as text, image, and a variety of alternate formats.
• Manage, process, analyze, and visualize data at scale to handle data where the conventional information technology fails.
• Match the methodological principles and limitations of machine learning and data mining methods to specific applied problems, and communicate the applicability and the advantages/disadvantages of the methods in the specific problem to nonexperts.
• Carry out the full data analysis workflow, including unsupervised class discovery, supervised class comparison, and supervised class prediction; summarize, interpret, and communicate the analysis of results.
• Organize visualization of data for analysis, understanding, and communication; choose appropriate visualization method for a given data type using effective design and human perception principle.
• Develop methods for modeling, analyzing, and reasoning about data arising in one or more application domains, such as social science, health informatics, web and social media, climate informatics, urban informatics, geographical information systems, business analytics, bioinformatics, complex networks, public health, and game design.

The data science MS degree empowers you to:

• Attain data scientist and data engineer positions in a fast-growing field
• Apply your skills to manipulate, store, visualize, and analyze data in any industry
• Pursue related doctoral degrees

Career Outlook

Students who successfully complete their master's in data science are qualified to seek jobs as:

• Data scientist
• Machine learning engineer
• Applications architect
• Enterprise architect
• Data architect
• Infrastructure architect
• Data engineer
• Business intelligence developer
• Data analyst

Employees with data science expertise are sought out in every industry, not just in technology. "Data scientists are highly educated—88 percent have at least a master's degree and 46 percent have PhDs—and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist," reports KDnuggets, a leading site on Big Data.