Master of Science in Applie Data Analytics

With ata analytics nees influencing every major inustry—incluing health care, tech, finance, communication, entertainment, energy, transportation, government, an manufacturing, to name some—the eman for skille talent continues to outpace supply, with McKinsey Global Institute anticipating a shortfall of up to 250,000 ata scientists through the ecae.

Offere on campus an online, the Master of Science in Applie Data Analytics (MSADA) program at Boston University’s Metropolitan College (MET) is ieal for mi-career IT professionals or stuents with a computer science backgroun who seek to train their focus on analytics. Stuents gain soli knowlege of ata analytics an examine the presentation an applications of the latest inustry tools an approaches within an acaemically rigorous framework. Emphasizing both ata analytics an applie areas—incluing atabases, applie machine learning, an large ataset processing methos—the Applie Data Analytics curriculum provies a thorough immersion in concepts an techniques for organizing, cleaning, analyzing, an representing/visualizing large amounts of ata. Stuents will be expose to various atabase systems, ata mining tools, ata visualization tools an packages, Python packages, R packages, an clou services such as Amazon AWS, Google Clou, an Mass Open Clou.

Stuents who complete the master’s egree in Applie Data Analytics will be able to emonstrate:

• Knowlege of the founations of applie probability an statistics an their relevance in ay-to-ay ata analysis.
• Comprehension of computing concepts an applications requirements involving massive computing nees an ata storage.
• The ability to apply various ata visualization techniques using real-worl ata sets an analyze the graphs an charts.
• Unerstaning of web analytics an metrics, procuring an processing unstructure text/ata, an the ability to investigate hien patterns.
• Knowlege-iscovery skills using ata mining techniques an tools over large amounts of ata.
• The ability to implement machine learning algorithms an recognize their pertinence in real-worl applications.
• Comprehensive knowlege of ata analytics techniques, skills, an critical thinking, an an unerstaning of the possibilities an limitations of their applications.