Data Science and Analytics, MS

(36 credits)

Program Description  

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Data analysts use business data from sources ranging from online dating, health care, transportation, industry, nuclear science, and many more to generate insights about populations and processes. Data analysis can be used to enhance productivity and increase profits, target medicines and treatments, optimize resource utilization, fight climate change, improve food production, and much more. Students will learn to understand and apply the foundational concepts and methodologies that constitute data analytics from basic statistics to data visualization to machine learning for descriptive and predictive purposes. This program prepares students to work across diverse industries and organizations. 

Learning Outcomes

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Upon completion of this program, students will be able to: 

• Design relational databases using best practice principles ; 
• Construct data using data science functions, selected programming languages, and associated data science libraries; 
• Interpret selected datasets using a variety of statistical tools; 
• Execute data mining operations on a variety of datasets;  
• Create data visualization presentations using selected datasets.

Internship

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The Internship course allows students to overlay the academic and theoretical study of Data Science and Analytics with practical experience in the field. Students have the means to apply academic concepts to solve real-world business problems.  Students will have a greater insight into a wide variety of operational issues that take place in professional organizations.  Students and their chosen Internship sponsor must be approved by the Program Director prior to the start of the internship. Internship courses have variable credit and are CT 5903 through CT 5904. A maximum of 8 credits of internship may be taken. Students cannot enroll in an internship until they have completed 20 credit hours of study at NEC.

• CT 5903 - Data Science and Analytics On-Site Internship I  
• CT 5904 - Data Science and Analytics On-Site Internship II     

Course Map

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Please visit the course map by term for this program here:  Data Science and Analytics, MS (On Campus; Online) Course Map