University of Wisconsin Program Designed For Busy Adults

by   |   December 4, 2015 2:30 pm   |   0 Comments

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The University of Wisconsin’s online master’s degree program in Data Science, launched in June, is designed for the ultimate in convenience for working adults, according to Dave Summers, the program manager.

“What’s different here is the flexibility, it’s a unique model,” he said. “Students select a home campus and then take two courses from each of our six campuses. They get the experience in computer science, math and statistics, management, and communication necessary for an interdisciplinary degree.”

Spring courses begin January 19.

In addition to flexible schedules, the program does not require applicants to take GMAT or GRE exams for admission.

Analytics professionals with relevant work experience or prior training are finding that a degree in data science provides them with the knowledge and skills necessary for a career in big data analytics. The University of Wisconsin online data science degree is designed to help fill this skills gap.

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“We know that employers need people with these kinds of skills,” said Summers, “so this degree makes students extremely marketable.”

The program is offered completely online. The 12-course, 36-credit program teaches students how to clean, organize, analyze, and interpret unstructured data, as well as how to derive knowledge from the data and to communicate these discoveries clearly using sophisticated data visualization techniques and other means.

Summers said the school’s extension program saw the need for big data analytics. “We knew it would be a great degree to offer our students,” he said. “And it’s meant for non-traditional students and their need for flexible schedules.”

In order to accommodate the busy schedules of working professionals, the program includes no on-campus meetings and no need to be online for classes at a specific time. In addition, students can access course content from any desktop, laptop, or mobile device.

“The program’s capstone program is an opportunity to bring students into real-world applications, either online or onsite, work through real data, get experience, and present it to a company,” Summers said.

Students work with R, Python, SQL Server as a database manager, Tableau for visualizations, and Hadoop. The Data Science Virtual Lab lets students access software and programming languages through an easy-to-use remote desktop – saving students the time and expense of having to buy and install these programs on their own devices.

“Our online courses are created by the same expert faculty using the same rigorous content and standards as on-campus courses,” Summers said. “That means you’ll graduate with the same recognized and respected UW degree as students who attend class on campus.”


Admission to the UW Master of Science in Data Science requires the following:

    • A bachelor’s degree and a cumulative grade point average (GPA) of 3.0. Official college transcripts are required. Students with a GPA of less than 3.0 may be considered for a provisional admission.


    • Prerequisite coursework in elementary statistics, introductory computer programming, and introduction to databases. Relevant work experience may be considered in lieu of this coursework.


    • Resume.


    • Two letters of recommendation (can be professional or academic).


    • A personal statement of up to 1,000 words describing the reasons behind your decision to pursue this degree and what you believe you will bring to the data science field. Space for the personal statement is included in the online application.


    • No aptitude tests (GMAT, GRE) are required.



Costs are the same for in-state and out-of-state students: $825 per credit (36 credits total).


DS 700: Foundations of Data Science

DS 705: Statistical Methods

DS 710: Programming for Data Science

DS 715: Data Warehousing

DS 730: Big Data: High-Performance Computing

DS 735: Communicating About Data

(for the following links, click and scroll down)

DS 740: Data Mining

DS 745: Visualization and Unstructured Data Analysis

DS 760: Ethics of Data Science

DS 775: Prescriptive Analytics

DS 780: Data Science and Strategic Decision-Making

DS 785: Capstone project

Susan Madrak is a Philadelphia-based writer.

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