Engineering Sciences MS: Focus in Data Science

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The MS program in Engineering Science with a focus on Data Science provides students with a core foundation in big data and analysis by obtaining knowledge, expertise and training in data collection and management, data analytics, scalable data-driven discovery, and fundamental concepts.

On this page:

Program Director

Johannes Hachmann
612 Furnas Hall
hachmann@buffalo.edu

Who is this for?

For engineering and natural/mathematical science students.

About Data Sciences

This applied program trains students in the emerging and high demand area of data and computing sciences. In fact, many surveys of employment have highlighted the great need for suitably trained professionals in these areas, estimating deficits of personnel availability in only the US at as high as 150,000 a year.

Students will be trained in sound basic theory with an emphasis on practical aspects of data, computing and analysis. Graduates will be able to serve the analytics needs of employers and will be exposed to several areas of application. The degree can be specialized using electives and a project. Classes will be modestly sized and emphasize best classroom practices while employing online resources to reinforce the classroom experience.

Students in this program will need some prior knowledge of mathematics, statistics and computing (commensurate with that from an engineering/natural science/math undergraduate program, see below for detail). The program can be completed in one calendar year of study.

The University at Buffalo has responded aggressively to these trends by first establishing a doctoral program in Computational and Data Sciences. UB has been a research pioneer in these areas and faculty have much expertise and decades of experience and assets like the world leading Center for Computational Research with unmatched facilities for big computing and data.

Entrance Requirements

Some prior knowledge of mathematics, statistics and computing (commensurate with that from an engineering/natural science/math undergraduate program) is required.

Undergraduate Grade Point Average:

Equivalent of a B average or better in a recognized undergraduate program; GRE: 300+ (waived for recent UB undergraduate students)

Math:

Calculus, Multivariate Calculus, Linear Algebra (e.g., UB course MTH 309)

Statistics:

Basic Statistics and Probability

Computer Science:

Programming (at least one language - C/C++/Python/Java), Data Structures (e.g., UB course CSE 113)

Degree Program Specifics

  • This program is currently taught in a cohort-based model and offers both Fall AND Spring admission.
  • Students will take a combination of core courses (18 credits), electives (6 credits), a data science survey + capstone course (3 credits) and the data science project (3 credits) for a total of 30 credits.
  • The program may be completed in one calendar year of study.

Course plan for full-time students:

  • First semester – 4 core courses (Math and Stats Basics)
  • Second semester – 3 core courses + 1 elective
  • Third semester – 1 Data Science Survey course + 1 Project/Capstone

Course Requirements

Core Courses (all are 3 credit hours each)

First Semester: Data Science Basics

Introduction to Probability Theory for Data Science (3 credits)
EAS 502 (see description below)

Introduction to Numerical Mathematics for Computing and Data Scientists (3 credits)
EAS 501 (see description below)

Statistical Data Mining I (3 credits)
EAS 506 (as of Fall 2018)

Programming and Database Fundamentals for Data Scientists (3 credits)
EAS 503 (see description below)

Second Semester: Data Analytics

Statistical Data Mining II (3 credits)
EAS 507 (as of Fall 2018)

Introduction to Machine Learning (3 credits) 
CSE 574

Elective 1 (3 credits)
See list below  

Data Models Query Language (3 credits)
CSE 560 (as of Fall 2018)

Third Semester: Project and Survey

EAS 504 Data Science Survey Course**

EAS 560 Data Science Project***

** The Data Science Survey Course will include weekly modules on application-oriented and other relevant topics, including: data science for bioinformatics, data science for health informatics, data science for engineering applications, ethics and privacy, and data science for finance.

*** Students will work with an affiliated faculty member on a Data Science Project. Projects will be sourced from industry where feasible.

STEM Approved

The Engineering Science programs are STEM approved, allowing international students the opportunity to apply for the 24-month STEM OPT extension.

The Institute for Computational and Data Sciences is temporarily suspending the GRE requirement for admission to our masters and PHD programs for the Spring 2021 and Fall 2021 entry terms.