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Master’s Degrees in Analytics

1 September 2012 No Comment

As you know, businesses have a lot of data to be analyzed, and that means companies everywhere are hiring statisticians. Consequently, universities have begun to develop degrees and certificate programs geared toward analytics.

These unique programs offer students hands-on experience so they are ready to enter the work force with the skills needed to succeed. In fact, companies such as Amazon.com, IBM, PayPal, and Walt Disney hire graduates from these programs soon after graduation.

A few such programs and their unique aspects are highlighted below.

University of Cincinnati
Department of Operations, Business Analytics, and Information Systems Carl H. Lindner College of Business Master’s in Business Analytics

Director: David Kelton, Master of Science in Business Analytics Program

The program is designed to provide a strong foundation in all the areas of business analytics, while allowing considerable flexibility so that students can tailor the course work and research project individually according to interest or career plans. The program has been in continuous operation for over 30 years (its former name was MS – Quantitative Analysis).

Program Features: Core courses in optimization, probability modeling, statistical methods, and simulation modeling.

Five to eight elective courses (depending on credit hours)—quantitative, technically oriented courses from a wide variety of areas such as optimization analysis, simulation analysis, statistical modeling, data mining, data visualization, statistical computing, forecasting and time series, multivariate methods, case studies, operations management, supply-chain management, finance, marketing, computer science, statistics, biostatistics, epidemiology, mathematics, and others both inside and outside the department and college.

A highly diverse, committee-based research project, in which each student is required to work closely with at least two faculty members to develop and report research with a significant business-analytics component or perform an acceptable application and analysis of business-analytics methodologies. The research project is required for all students.

A career service office that helps each student promote their individual strengths by providing opportunities for professional development.

Length: Full-time is 2–3 semesters or 9–12 months. This program is also available part-time.

Who Should Apply: Students who have a strong prior foundation in mathematics (three semesters of calculus plus a course in linear algebra); basic business knowledge is also required, but can be taken during the program as needed. View the detailed prerequisite list.

Unique Aspects: While our program has significant statistical content in both the required core courses and the electives, it also contains significant core and elective material in operations-research topics (optimization, simulation, and stochastic processes). We also offer electives that bridge those two fields, such as statistical computing, data visualization, and applications development using VBA. Students also can take up to half of their electives outside our department, in fields such as computer science, information systems, engineering, biostatistics, marketing research, and finance.

North Carolina State University
Institute for Advanced Analytics, Master of Science in Analytics

Director: Michael Rappa, Advanced Analytics, Founding Director and Distinguished University Professor

The Master of Science in Analytics (MSA) prepares students for quickly deriving insights from a vast quantity and variety of data.

Program Features: A team-based learning experience called “the practicum” gives students the opportunity to conduct real-world analytics projects using data from sponsoring organizations. Students work in teams of 4–5 to understand the business problem and then clean and analyze the data. The practicum spans seven months and culminates with a report and presentation to the sponsor.

Classes are developed exclusively for the program and include data mining, text mining, forecasting, optimization, databases, data visualization, data privacy and security, financial analytics, and customer analytics, as well as communication and teamwork skills.

Length: Full-time, 10 months

Who Should Apply: Applicants must hold a bachelor’s degree from an accredited college or university and have a proven track record of strong academic performance. It is not uncommon for applicants to already hold advanced degrees. Applicants come from a variety of academic majors. However, prospective students who have not majored (or minored) in mathematics or statistics will need to have successfully completed prerequisites in these subjects to be admitted. Students also can do a self-assessment online to see if the program is right for them.

Unique Aspects: The MSA program is a fully integrated curriculum, not simply a menu of core and elective courses, which pulls together faculty and subject matter from across several departments and colleges. While a graduate program in statistics would focus predominantly on topics within statistics, the MSA is a blend of applied mathematics, statistics, computer science, and business disciplines. Furthermore, the program has a strong professional orientation that prepares students for careers in industry. Students work with real data in a team context and receive extensive training and coaching in practical matters such as teamwork, leadership, and communication skills. As a result, graduates are in high demand by a wide range of employers. The MSA has an unmatched five-year track record of placing more than 90% of its students in well-paying positions by graduation.

Northwestern University
Department of Industrial Engineering and Management Sciences McCormick School of Engineering, Master of Science in Analytics

Director: Diego Klabjan, Associate Professor, Industrial Engineering and Management Sciences

Program Features: The program serves two main audiences: students and industry. We seek to provide students with the skills they need for a fulfilling career in analytics while also satisfying the needs of industry for highly skilled staff.

This program teaches the skills that drive business success and produces exceptional analysts who can lead project teams able to fully understand and clearly communicate the business implications of their work.

Graduates of the Master of Science in Analytics will be able to do the following:

  • Integrate information technology and data science to maximize the value of data
  • Communicate clearly and persuasively to a variety of audiences
  • Identify and assess the opportunities, needs, and constraints for data usage within an organizational context
  • Design innovative and creative data analytics solutions
  • Lead analytics teams and projects

The program is highly selective—only 30 students. The aim is to build a high-quality program, rather than a large one. The focus is on collaboration, rather than competition within the cohort. Therefore, there is lots of teamwork (reflects professional reality), which helps build a ready-made professional network.

All three areas of data analysis are studied: predictive (forecasting), descriptive (business intelligence and data mining), and prescriptive (optimization and simulation).

The program also includes a summer internship placement in which each student spends three months contributing to an actual project team, choosing from a variety of industries.

During their final quarter, students participate in the capstone design project, in which they work in teams to develop a business solution to a current real-world problem provided by a U.S. company.

The Master of Science in Analytics program also provides training in SAS, SPSS, Tableau, Cognos, and Hadoop. Students will use all during the program.

The Master of Science in Analytics offers merit-based fellowships to its most outstanding applicants; is housed within the top-five–ranked department of industrial engineering and management sciences (IEMS); and draws upon the faculty of IEMS as well as Northwestern’s considerable resources, including the departments of electrical engineering and computer science, integrated marketing communications, and the Kellogg School of Management.

Approximately one-third of the program instructors are current industry professionals.

Length: Full-time, 15 months

Who Should Apply: Students who have bachelor’s degrees in engineering, business, computer science, math, information technology, and a number of other academic disciplines. No specific undergraduate degree is required, but a background in one of the above areas is encouraged. We are looking for savvy students who can demonstrate an aptitude for quantitative material and show potential for being able extract the value of the data and communicate it to a variety of audiences.

Unique Aspects: The Master of Science in Analytics contrasts with traditional graduate programs in statistics in that it is highly applied, focusing on preparing students for both immediate employment and a lucrative and rewarding career in data analytics.

Also, the program offers unique and innovative classes such as “Analytics for Big Data” and “Data Visualization” and incorporates a summer internship placement and industry-supplied design projects for which students are responsible. The courses are highly applied, making use of industry-supplied data from real-world situations. With regular guest lecturers and our industry professionals’ seminar series, students have frequent touch-points with those who are at the leading edge of applying analytics today.

Finally, the program offers a diverse range of industry collaborators, including IBM, SAS, and Teradata.

University of San Francisco
Master’s in Analytics

Director: Terence Parr, parrt@usfca.edu

The MS in analytics is an innovative, multi-disciplinary program offered jointly by the college of arts and sciences and the school of management that provides students with the skills necessary to develop techniques and processes for data-driven decisionmaking—the key to effective business strategies.

The USF Analytics Program delivers training in both the techniques and skills required to analyze structured/unstructured big data to derive meaning and drive business decisions. Graduates become data scientists and analysts in finance, marketing, operations, business intelligence, or other groups generating and consuming large amounts of data.

Students study topics such as data mining, machine learning, statistical models, predictive analytics, econometrics, optimization, risk analysis, data visualization, business communication, and management science. They learn to acquire, filter, clean, organize, and store data using Python and SQL/NoSQL as “glue” between data sources and statistical tools such as R and SAS. The focus is on applying mathematics, statistics, and computer science to solve real problems.

Training goes beyond the hard skills to teach students to work effectively in teams and communicate analytical results in business settings. The analytics program is designed for students with a strong background in one or more of the following areas: math, computer science, engineering, or economics.

Program Features: The program begins in early August with a month-long intensive foundation—three one-week modules that establish the core skills required to succeed in the program. These modules cover (1) probability, statistics, and mathematics; (2) programming in SQL, Python, and R; and (3) economics, accounting, and strategy.

An ongoing practicum project takes place, in which groups of students work in small teams on real-world data sets, perform comprehensive analysis, and develop reports and recommendations in preparation for a presentation to meet the goals established by our business “clients.” The practicum is where students apply the knowledge they have learned in the program. The practicum is also where students work with mentors to develop the professional skills they need to succeed in a business setting. Companies associated with our advisory board sponsor the practicum projects.

Length: 11 months. The application date for priority admission and scholarship consideration is May 1 of each year.

Who Should Apply: Applicants with academic or professional backgrounds in math, computer science, engineering, finance, economics, or equivalent skills are encouraged to apply. Applicants who hold a bachelor’s degree in any field and have fulfilled the foundation requirements/equivalencies are considered for admission.

Unique Aspects: The MS in Analytics program is explicitly interdisciplinary. It is a joint program between the computer science department and the school of management, bringing together faculty from computer science, mathematics, economics, and business.

Our analytics program provides training in computer science, statistics, and business analytics with a focus on practical applications in finance, marketing, operations, and strategy. It has a broader, more practical orientation than traditional graduate programs in statistics.

The newest wave of big data firms and startups demand data scientists who can mash up and analyze disparate data types and sources that are often beyond the capabilities of traditional analytics software. Unlike other graduate programs in analytics, our focus is on open-source programs for manipulating and analyzing all the types of data inherent in today’s business opportunities. Students in the program will complete certification workshops in Python and R, as well as more conventional software such as SAS and MATLAB.

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