Graduate Programs in Applied Data Science

Our five affordable graduate programs in Applied Data Science can be completed online, in person, or hybrid. The two-year Master’s program and four graduate certificate programs prepare students to collect, analyze, and report on big data effectively and ethically. These programs provide real-world application and paid field experience with leading data-driven companies. With 100% job placement and a $95k median salary, the MS in Applied Data Science program is a great return on your investment.

New! Graduate Certificate Programs Now Available

New College is pleased to offer four graduate certificates designed to provide you with valuable educational experience in a more accessible, focused format than a traditional master’s degree program. They include: Data Analysis and Visualization with R, Machine Learning with Python, Statistical Modeling, and Distributed Computing. Plus, you can transfer your graduate certificate credits to apply toward the Master’s degree program in Applied Data Science. Learn More

Master’s in Applied Data Science Program

The M.S. Applied Data Science graduate program is a two-year 36-credit program, which includes 11 full-semester 3-credit courses, two required practicums (one being a full-semester 3-credit course), industrial seminar series in the first three semesters and industrial workshops during the January interterm. The curriculum offers a blend of interdisciplinary theory and practical application of skills through courses, such as Exploratory Data Analysis, Applied Machine Learning, and Data Visualization. Our students gain experience applying both Python and R to develop solutions for our corporate partners as a part of the rigorous curriculum.

In the final semester, students will implement their skills and obtain industry experience with a paid practicum working full-time as part of a data science team at one of our corporate partners, or at another company or organization of their choice. The practicum course will be completed under Data Science faculty supervision and is a required component of the program.  At the end of the program, students would have gained the industry knowledge, technical skills, and real-world experience required to start their successful careers.

“Students can expect a very well-rounded education from the data science program. Whether it be in algorithms, statistics or general programming, you’ll have all the things you’ll need to be successful as a data scientist.”

Adam Lashley
M.S. in Applied Data Science Student

What do Students and Alumni Say?

Ashley Brockway Class of 2021 "I applied to the Data Science program to expand my toolkit working with data. I increased my confidence in computer programming and statistics, and was able to apply theoretical material in self-directed projects with my classmates. I expanded my network by meeting with alumni and bonding with my cohort over homework and group study sessions. At a high level, the program is job-focused but, in my experience, I learned strong problem-solving skills that can be applied across many projects in both work and life."
Adriana Souza Data Scientist TechData Corp, Class of 2019 "My favorite thing about the graduate program was the fact that it was a cohort-based education. We were all from different backgrounds. Me, coming from a math and economics background, I wasn’t the best programmer. So, I needed to lean on others around me to help me build those skills up and I used my math skills to help others who didn’t come with as much math. Being so close to my colleagues and professors was a really wonderful experience."
Tanner Robart Data Scientist Researcher U.S. Department of Transportation, Class of 2017 "The graduate program at New College were some of the best years of my life. I learned technical skills that still enable me to work in modern and cloud based computing environments. Getting so much 1 on 1 time to work and talk with my professors made sure I always had resources and help when I needed it. Working with real businesses provided hands-on consulting experience and a broad exposure to the diverse practices and needs of clients."

Career Pathways

  • Researcher
  • Data Scientist
  • Machine Learning Engineer
  • Applications Architect
  • Data Architect
  • Business Intelligence Developer
  • Statistician
  • Data Analyst

Exceptional Return on Investment

Affordable Tuition

$95k

Median Post-Graduate Salary

100%

Graduate Field Placement within 3 months

Affordable Tuition

Fall 2022 Applications Now Available

Are you ready to pursue an in-demand, high-paying career changing the world through big data? Start your application today! Apply Now

Admissions Info

Real-World Experience

Our curriculum is developed with our corporate partners and industry experts as the applications of big data evolve. Students will get hands-on experience with real data sets from a variety of industries, and complete a paid, full-time practicum, often with our partners or an organization of their choice.

Corporate Partners

Allen Institute for Brain Science

LexisNexis Risk Solutions Groups

Novetta

HPCC Systems

Riff Analytics

Advisory Board

See the executives and professionals committed to enhancing knowledge and practice of Data Science and Business Analytics for our program as part of the M.S. Applied Data Science Advisory Board. 

First Semester Courses

The state-of-the-art curriculum blends theory and practice. Over four semesters students in the small-cohort program are guided by our values of academic rigor, dedication, practical relevance, and teamwork.

The bootcamp aims to equip all students entering the graduate program with introductory skills and knowledge needed to conduct further coursework in the program. This will help students from diverse backgrounds to have a common knowledge base as a cohort. Topics will include review of Python and R programming, common data science tools, resources and platforms, operating systems, database concepts and systems, among others. The Bootcamp is offered during the week of new graduate student orientation. It is a 3-day intensive course.

Exploratory data analysis in the context of knowledge discovery, including the use of data visualization software. Practical skills for working with large datasets including common methods for gathering, organizing, and reshaping structured and unstructured data, with an introduction to related methods in R, and some examples in Python.

Fundamentals of algorithms and measures of performance. Taught in Python, the course includes an exploration of efficient algorithms for sorting and retrieving data, graph algorithms and combinatorial optimization, dynamic programming, randomized algorithms and approximation algorithms.

A statistics course focusing on descriptive and inferential statistics, with topics on linear regression, confidence intervals and hypotheses testing, including probability theory and modern approaches such as resampling, with all methods illustrated in R and a focus on methods relevant for data science using industrial datasets.

Project-based course with a coverage of supervised and unsupervised learning and an emphasis on working with real industrial data. Bayesian analysis and other specific learning paradigms including regression, clustering, random forests, support vector machines, kernel methods, and neural networks.

Seminar series which hosts professionals and executives as guest speakers from a variety of industrial domains. Each weekly or biweekly seminar covers topics and applications to diverse problems in business via applications of various data science techniques.

Data Science in the News

MS Applied Data Science Faculty & Staff

Nikita Bagley Assistant Director of Graduate Admissions
Contact 941-487-4103 nbagley@ncf.edu
Office or Division Applied Data Science Graduate Program Admissions
Burcin Bozkaya Director of Applied Data Science Graduate Program
Professor of Data Science
Contact (941) 487-4173 bbozkaya@ncf.edu
Office or Division Applied Data Science Graduate Program Natural Sciences Division Area of Concentration Data Science
Bernhard Klingenberg Professor of Statistics
Contact (941) 487-4172 bklingenberg@ncf.edu
Office or Division Applied Data Science Graduate Program Natural Sciences Division
Matthew Lepinski Associate Professor of Computer Science
Contact (941) 487-4660 mlepinski@ncf.edu
Office or Division Applied Data Science Graduate Program Natural Sciences Division
Ann Masterman Executive Director of New Student and Graduate Admissions
Contact 941-487-4750 amasterman@ncf.edu Schedule a Meeting
Office or Division Admissions Applied Data Science Graduate Program
Patrick McDonald Professor of Mathematics
Contact (941) 487-4375 mcdonald@ncf.edu
Office or Division Applied Data Science Graduate Program Natural Sciences Division
Tiago Perez Assistant Professor of Data Science
Contact (941) 487-4519 tperez@ncf.edu
Office or Division Applied Data Science Graduate Program Natural Sciences Division
Jack Reilly Associate Professor of Political Science
Contact (941) 487-4578 jreilly@ncf.edu
Office or Division Social Sciences Division Applied Data Science Graduate Program
Tania Roy Assistant Professor of Human Centered Computing
Contact (941) 487-4369 troy@ncf.edu
Office or Division Applied Data Science Graduate Program Natural Sciences Division
Tyrone Ryba Associate Professor of Bioinformatics
Contact (941) 487-4228 tryba@ncf.edu
Office or Division Natural Sciences Division Applied Data Science Graduate Program
Andrey Skripnikov Assistant Professor of Applied Statistics
Contact (941) 487-4515 askripnikov@ncf.edu
Office or Division Natural Sciences Division Applied Data Science Graduate Program

Accreditation

New College of Florida is accredited by the Southern Association of Colleges and Schools Commission on Colleges to award Bachelor’s degrees and Master’s in Applied Data Science degrees.

Contact the Commission on Colleges at 1866 Southern Lane, Decatur, Georgia 30033-4097, telephone 404-679-4500, at www.sacscoc.org for questions about the accreditation of New College of Florida.

Catalog & Academic Calendar

Graduate Catalog 2022-2023

Graduate Academic Calendar 2022-2023