Data Science, M.S.
Our networked world is drowning in data, affecting the way business, government, science, and healthcare are conducted. The NYIT Data Science, M.S. is designed to help professionals and researchers sort through this data tsunami, by providing a fundamental understanding of the methods and algorithms of data science.
By the end of our 30-credit program, graduates will have the skills and knowledge to transform data into relevant insights for making better business decisions by:
Employing data science concepts and methods to solve problems in business and scientific contexts and to communicate these solutions effectively.
Using computing theory, languages, and algorithms, and mathematical and statistical models to formulate and implement data analyses.
Applying ethical practices in everyday technical and business activities to make ethical decisions with respect to the design and use of data management tools.
Test classroom theory in the school's labs. From vacuum ovens to wind tunnels, you'll access the same equipment used by industry professionals.
4832970 / Pixabay
DTSC 610 Programming for Data Science (3 credits)
DTSC 615 Topics in Optimization (3 credits)
DTSC 635 Probability and Stochastic Processes (3 credits)
DTSC 701 Introduction to Big Data (3 credits)
DTSC 710 Machine Learning (3 credits)
Total: 15 Credits
Students must choose either Thesis or Non-Thesis/Project track:
DTSC 890 MS Thesis I (3 credits)
DTSC 891 MS Thesis II (3 credits)
Electives: Consult with program chair/program advisor on any electives. (9 credits)
Total: 15 Credits
DTSC 870 MS Project I (3 credits)
Electives: Consult with program chair/program advisor on any electives. (12 credits)
Total: 15 Credits
Total Required Credits: 30
An NYIT degree is your passport to an exciting future in an in-demand field. Possible career opportunities for graduates with this degree include:
Tuition, Scholarships, & Financial Aid
We believe it's important to offer access to the opportunity for all qualified students. NYIT has one of the lowest private tuitions in New York State and provides more than $40 million in institutional financial aid each year.
B.S. degree or its equivalent from an accredited college or university in computer science or related area
If students have a degree in engineering, an accredited program is one that is accredited by the Engineering Accreditation Commission of the Accreditation Board for Engineering and Technology (ABET).
If students have completed degrees in computer science or a closely related field, an accredited program is one taken at a college that is regionally accredited, such as the Middle States Commission on Higher Education.
If students have an international baccalaureate degree or diploma, which is equivalent to three years of undergraduate study in the U.S. in computer science, engineering, or a related area, they may be eligible to be admitted into a bridge option in the intended graduate program.
Since the M.S. in Data Science is a new program, international students requiring an F-1 visa are not currently eligible for admission to the Data Sciences, M.S. for the spring 2019 semester. We encourage you to apply for a future term or to reach out to an admissions advisor to discuss other options. Please contact our admissions team at email@example.com for more information.
Minimum undergraduate CGPA in undergraduate studies of 2.85 for full matriculation
Applicants who do not qualify for full matriculation and have an undergraduate GPA between 2.5 and 2.84 may, at the discretion of the director, be given the opportunity to demonstrate qualifications for full matriculation by achieving a GPA of 3.0 or higher in the first four graduate courses. In addition, such students may be required to take one or more parts of the GRE and meet individual departmental requirements. In general, students in this category will not be permitted to continue in the program for more than two semesters unless they have qualified for fully matriculated status, or there are special extenuating circumstances.
Submit GRE scores
Graduates of foreign universities are required to take the GRE and submit their scores.
Students with a GPA below 2.85 may, at the discretion of the dean, be asked to take the GRE or other diagnostic tests. Admission will be based upon consideration of test results, previous academic performance, and related employment, if applicable.
Students with insufficient background for admission into the Data Science M.S. program may be admitted if they have satisfied the following prerequisites or equivalents before taking any graduate-level courses in the program:
CSCI 125 Computer Programming I (3 credits)
CSCI 185 Computer Programming II (3 credits)
CSCI 235 Elements of Discrete Structures (3 credits)
CSCI 260 Data Structures (3 credits)
CSCI 270 Probability and Statistics for Computer Science (3 credits)
CSCI 300 Database Management (3 credits)
CSCI 312 Theory of Computation (3 credits)
CSCI 335 Design and Analysis of Algorithms (3 credits)
Additional Prerequisite Courses
MATH 170 Calculus I (4 credits)
MATH 180 Calculus II (4 credits)
MATH 310 Linear Algebra (3 credits)
Note: Credits earned for the courses above will not be counted toward the 30 credits required for the degree.
$50 nonrefundable application fee.
Copies of undergraduate transcripts for all schools attended. All final, official transcripts must be received prior to the start of your first semester.
Copy of college diploma or proof of degree.
Official GRE scores, if required (NYIT GRE Code: 2561).
International student requirements: English proficiency, I-20, and transcript evaluation (International students on an F-1 visa are not currently eligible for admission to the Data Sciences, M.S. for the spring 2019 semester. Please contact our admissions team at firstname.lastname@example.org for more information.)
Students may transfer up to six transfer credits from an accredited graduate program for appropriate courses in which a minimum grade of B was earned.