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Master of Science in Data Science – Concentration for Computer Scientists Courses

Combine data mining skills and biological understanding to solve pressing problems in the life sciences

Courses in the M.S. in Data Science Concentration for Computer Scientists are designed to give students the technical savvy to design front-end systems and the mathematical skills to write algorithms that decipher large quantities of data. The concentration requires four courses: 70-590 and three elective courses.

Choose three (3) of the following courses:

70-517 Pervasive Application Development (3)

Development of web- and mobile-based front ends for large-scale data systems, with a focus of portability, accessibility, and intuitiveness.

YOUR OPPORTUNITY: Ubiquitous data requires ubiquitous computing. This course teaches you how to create applications that run on mobile and non-traditional platforms.

Prerequisite: 70-511

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70-550 Machine Learning (3)

Algorithms for enabling artificial systems to learn from experience; supervised and unsupervised learning; clustering, reinforcement learning control. Students will write programs that demonstrate machine-learning techniques.

YOUR OPPORTUNITY: Data analysis software must dig through data with little guidance, which requires techniques for detecting and learning from cues automatically. You will learn how to code such systems.

Prerequisite: 70-511

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70-552 Semantic Web (3)

Expressing relationships among items in a way that enables automated, distributed analysis in an application-independent way; text mining to derive meaning from semantic networks; algorithms for processing semantic networks; developing a web of things.

YOUR OPPORTUNITY: You will learn how to integrate data from sensor networks and other non-traditional systems to create pervasive data science solutions.

Prerequisite: 70-511

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70-555 Distributed Computing Systems (3)

Architecture and programming of parallel processing systems; distributed data storage techniques; multithreading and multitasking; redundancy; load balancing and management; distributed system event logging; programming techniques for maximizing the importance of distributed systems.

YOUR OPPORTUNITY: You will learn how to leverage parallel and distributed computing architectures to process data on a massive scale.

Prerequisite: 70-511

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And conclude with the following capstone experience:

70-590 Data Mining and Analytics Project for Computer Scientists (3)

The capstone experience for students pursuing the Computer Science concentration in Data Science. Students will develop a solution to a real-world problem in data science, document their work in a scholarly paper, and present their methodology and results to faculty and peers.

YOUR OPPORTUNITY: You will demonstrate your skills as a data scientist by implementing a project that helps an organization make sense of the data it has collected.

Prerequisite: A minimum of 24 hours earned in the MS-DS program.

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Take the Next Step

Learn more about the online M.S. in Data Science degree program at Lewis University. Request more information or call us today at (866) 967-7046.