Data Engineering

The Master of Science program in Data Engineering allows students from STEM disciplines to focus their analytical, programming and engineering skills to integrate messy data into clean, usable datasets; organize, retrieve large data efficiently, and creatively solve data-related analytical problems.

UNT's degree is interdisciplinary, allowing students to leverage their existing skill set and experience by combining it with skills in data engineering. Graduate students in our program have the opportunity to focus their entire degree on data engineering or specialize in biomedical engineering. This is a STEM-designated master's program.

View downloadable flier to learn more.

According to the Dice 2020 Tech Job Report, jobs in data engineering are growing by 50% each year, making data engineering the fastest growing job in technology in 2019.

What to expect

Students can expect to take 15 hours of core courses, 3 hours of predictive analytics coursework, and 15 hours in their chosen concentration.

Core courses give students a solid foundation in data engineering and will dive into big data, data analytics, data visualization, and database systems.

Concentration areas focus on data engineering and biomedical engineering.

Students who graduate from this program will be able to:

  • Build and maintain data pipeline systems
  • Improve data reliability, efficiency, and quality
  • Prepare complex datasets to solve difficult problems
  • Understand efficient algorithms and data structures
  • Apply data engineering skills to their field of study

 

Course offerings

Core Courses | 15 Hours
  • CSCE 5300: Introduction to Big Data and Data Science
  • CSCE 5310: Methods in Empirical Analysis
  • CSCE 5320: Scientific Data Visualization
  • CSCE 5350: Fundamentals of Database Systems
  • CSCE 5370: Distributed and Parallel Database Systems
Predictive Analytics Course | 3 Hours (Choose one course from the list below)
  • CSCE 5215: Machine Learning
  • CSE 5216: Pattern Recognition
  • CSCE 5380: Data Mining
General Data Engineering Concentration | 15 Hours (Students choose 5 courses from the list below)
  • CSCE 5290: Natural Language Processing
  • CSCE 5200: Information Retrieval and Web Search
  • CSCE 5170: Graph Theory
  • CSCE 5215: Machine Learning 
  • CSCE 5216: Pattern Recognition
  • CSCE 5230: Methods of Numerical Computations
  • CSCE 5360: Implementation and Practices of Database Systems
  • CSCE 5380: Data Mining
  • CSCE 5390: Multimedia Computing
Biomedical Engineering Concentration | 15 hours (Students choose 5 courses from the list below)
  • BMEN 5007: Research Methods in Biomedical Engineering
  • BMEN 5322: Medical Imaging
  • BMEN 5315: Computational Methods in Biomedical Engineering
  • BMEN 5700: Introduction to Statistical Genetics
  • BMEN 5800: Topics in Biomedical Engineering
  • BMEN 5900: Special Problems in Biomedical Engineering

 

Choose your career path

While estimates vary, a recent report from O'Reilly states companies typically need a minimum 2-3 data engineers for every data scientist to successfully complete projects, and the current job market is struggling to keep up with this demand. Our M.S. in Data Engineering program prepares students to enter this thriving job market right out of college.

The most in-demand jobs are data engineers, data architects, business intelligence architects, machine learning engineers, and data warehouse engineers/developers, with many data engineers working in many different fields.

Marketable Skills gained from this program include:

  1. Efficiently visualize data
  2. Effectively communicate technical information
  3. Quickly adapt to new technologies
  4. Collaborate to solve problems
  5. Understand and use data software

 

Admissions

Our program is open to high-achieving students from engineering, computer science, math, and science-related backgrounds. Each applicant's transcripts will be reviewed to determine if their background is suitable for admission into the concentration of their choice and/or if leveling coursework is required. If leveling coursework is needed, students may be required to take undergraduate leveling courses to prepare for coursework in the concentration of their choice.

To be admitted, students should:

  • Have a 3.0 or higher GPA from a degree program in a STEM discipline.
  • Have taken statistics or linear algebra and have prior programming experience using languages like C++, Java, Python, R, or Matlab.
  • Supply GRE scores. GRE may be waived for graduates of UNT.
  • Have a 79 or higher on TOEFL, a 6.0 or higher on IELTS, or otherwise meet the university requirements for English language proficiency (if international)
  • Provide a resume to reflect experience in data, programming, research, etc. (optional)

To learn more, email kathryn.beasley@unt.edu.

Apply by January 15th to be considered for all funding opportunities.

 

Funding your degree

Teaching and research assistantships provide support for many graduate students. In addition to a monthly stipend, assistantships also qualify students for in-state tuition rates, and many students receive tuition and fee support. Scholarships are available to graduate students as well. The general scholarship deadline is March 1 of each year. The College of Engineering also offers scholarships to qualified students throughout the year.

For more information about tuition, visit the online tuition calculator.