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Data Science Education at NCSU: Education with a Mission

By   /  May 24, 2016  /  No Comments

logoNCSUThe Master of Science in Analytics (MSA) at North Carolina State University (NCSU) is one of the oldest Data Science degrees in the country. The program began in 2007, with the school’s Institute for Advanced Analytics focused on supporting the success of its students. A presentation about the program at the school sets its ambitions high: “Our mission is to produce the world’s finest practitioners of analytics.”

The program was created and is still overseen by Dr. Michael Rappa, who proposed creating the program in April 2006.

“The impetus for the proposal came from my work over the prior decade in the field of web analytics and the need to produce students with the skills to address the challenges of large volume, fast streaming numerical and text data,” he said via e-mail. “We are in many ways the template for dozens of programs that followed. About 150 universities have visited us over the past decade, and we share the blueprint for our curriculum openly.”

As Dr. Rappa explained, “The focus of the MSA is centered on practice. We approach theory in the curriculum only to the extent it may be a necessary prerequisite to understanding how to best apply a method.”

An Intensive Course of Study

To achieve its goals, Institute students complete a concentrated, 10-month, full-time course of study; there is no part-time or online option. Full-time study here is equivalent to a full-time job; Dr. Rappa described it as a Monday to Friday, 9 to 5 commitment for their students.

During their studies, students take a series of unique courses, taught by the Institute’s faculty and exclusive to the Institute and to the MSA students.  The tuition is subsidized for North Carolina residents, at approximately $25,000. For out-of-state students, tuition and fees are about $43,000:

“The MSA is designed to give students broad exposure to the methods, tools, and application of analytics,” Dr. Rappa said. “The curriculum is a fully-integrated team-driven model with a unique process for individualized feedback and coaching.”

The Institute has its own faculty and draws on other university departments as needed, bringing them to the Institute on a limited basis. Courses cover material from applied mathematics, statistics, computer science, operations research, Data Science, and business including analytical methods such as data mining and text mining, along with applications such as financial analytics and customer analytics.

Students also learn about data privacy and security requirements. Students learn to use popular software used in industry, such as SAS; students often qualify for vendor certifications, with some students obtaining multiple certifications.

The curriculum is intended to meet employers’ needs, so the non-technical skills needed for success in business, such as technical writing, presentation skills, and teamwork, are also covered.

The 30 credits are taken two courses at a time, over the summer, fall, and spring semesters. Summer courses teach tools and provide a foundation for analytics studies with topics including databases and statistical programming; the fall and summer courses teach methods and application such as optimization, time series and forecasting, and experiment design – they also include the analytics practicum.

The practicum is the cornerstone of the program: a team project, which lasts for eight months beginning in the fall semester. Student teams work on real-world projects suggested by industry and government partners and use up to 2TB of real data from those organizations. There have been more than 100 projects and more than 70 sponsors since the MSA program began, with industries including advertising, banking, sports, travel, manufacturing, healthcare, and more. Current sponsors include Disney and the Central Intelligence Agency.

Confidentiality agreements prevent Dr. Rappa from speaking in much detail about the projects:

“I can say the projects are very wide ranging, very challenging, and can have significant business impact. One of the more interesting projects this year is a consortium of seven art museums led by the North Carolina Museum of Art. It focuses on developing a predictive model for special exhibition attendance,” he shared.

The practicum assigns teams for four or five members to understand the business problem and prepare and analyze the provided data. At the end of the project, the team creates and presents a report to the sponsor, which then owns the results.

Admissions and Prerequisites

Though the class is large, with 120 students annually, admissions are highly competitive; there are more than 1,000 applicants annually. Standardized entrance exams, such as the GRE and GMAT, are not required. All students must have an undergraduate degree. There is no required or preferred undergraduate major, but the bulk of students majored in math, statistics, engineering, science, business, economics, or finance.

Students must have a significant background in mathematics and statistics. The Institute suggests two semesters of undergraduate statistics work, including substantial study of regression analysis.

The Institute offers an online self-assessment to help prospective students evaluate their knowledge of statistics. To avoid discouraging interested students who came to their interest in Data Science late, the Institute allows those who don’t have the prerequisites to take prerequisite courses at the Institute. Interested students apply to the program first, attend the prerequisite courses, and are evaluated for admission after completion.

About half of students completed their undergraduate degree within two years of enrolling; the rest have as many as 30 years of work experience. Close to one-fifth already have a graduate degree, including PhDs. About 40 to 45 percent are women. Most of the students, 85-90 percent, are U.S. citizens, but students have come from more than 40 different countries. Of the U.S. citizens, close to half are North Carolina residents.

Employment After Graduation

The school assists students with professional and career development, providing help with writing resumes, improving interview schools, and professional networking. The Institute’s graduates have a solid employment record; benchmarks show placement rates as good or better than comparable programs at other top universities. Dr. Rappa reported that typically 100 percent of students received at least one job offer by graduation:

“We host more than 1,000 initial job interviews on-site with about 50 employers each year. Between 90 – 95 percent of the students will find employment through our onsite process. The remainder will connect with jobs through independent search efforts.”

The process of connecting with employers begins early; the school holds employer information sessions in September, places student profiles online by October, and sends student resumes to employees by December. Interviews on campus begin in January, and students, who will graduate in May, typically have employment offers by March.

The students find work in a range of job titles, including Analyst, Data Scientist, Developer/Modeler, and Consultant; some take management or executive-level positions. Employers include startups and established multinational corporations in all economic sectors including banking, insurance, government, pharmaceuticals, retail, legal services, and entertainment. The average starting salaries are about $100,000; the school reports the average ROI payback period is 20 months.

Because the MSA is recognized as a STEM degree, international students who receive the MSA degree qualify for Optional Practical Training employment, allowing them to extend their stay in the U.S. for temporary employment.

Undergraduate Data Science Studies at NCSU

The Institute for Advanced Analytics offers only graduate-level courses. The Computer Science and Statistics departments jointly teach a survey course for undergraduates, covering topics such as data structures, data mining, and data visualization.

Photo Credit: North Carolina State University

About the author

Elissa brings a practitioner's insight to her writing about information technology. She holds a B.A. in Computer Science from Cornell University and an M.S. in Computer and Systems Engineering from Rensselaer Polytechnic Institute, where her thesis dealt with testing expert systems. Before becoming a writer, she put her technical training to use as a software developer and project manager at a defense consulting firm, a major telecommunications company, and one of the largest financial institutions in the United States.

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