Program Overview

Program Overview

The Data Analytics Engineering (MS) program is a multidisciplinary program offered by the College of Engineering and Computing at George Mason University. This 100% online program has a duration of 2 years and requires 30 total credits. The cost per credit is $930, and the program is accredited by the SACSCOC.

Program Description

The Data Analytics Engineering (DAEN) Master of Science Program provides students with knowledge and experience across a broad range of data analytics algorithms, tools, and processes. The program focuses on a flexible and broad set of courses to be used by graduates for solving a wide range of real-world problems. The online program can potentially be completed in approximately two years and will provide the graduate with an expanded set of career options and opportunities.

Unique Features

• The program addresses three types of data analytics engineering:
  • Data engineering
  • Data architecture
  • Data analysis
• The data engineering area of the program is focused on data conditioning required to fit data into specific data architectures and transform data to be exploitable.
• The data architecture area is focused on creating frameworks that make data-driven intelligence possible.
• The data analysis area is focused on creating repeatable means to draw key insight and signal from data.
• In the capstone course, students will create a functional team project and deliver a technical report and oral briefing at its completion.

Curriculum

The multidisciplinary curriculum includes coursework from several departments within the College of Engineering and Computing. The program requires:

• 15 credits in required courses
• 15 credits in elective courses Required courses include:
• AIT 580 Big Data to Information
• CS 504 Principles of Data Management and Mining
• OR 531 Introduction to Analytics and Modeling
• STAT 515 Applied Statistics and Visualization for Analytics
• DAEN 690 Data Analytics Project

Elective Courses

Elective courses are available in various categories, including:

• DAEN Elective Courses
  • DAEN 698 Independent Research
• IST Elective Courses
  • AIT 524 Database Management Systems
  • AIT 526 Introduction to Natural Language Processing
  • AIT 614 Big Data Essentials
  • AIT 622 Determining Needs for Complex Big Data Systems
  • AIT 624 Knowledge Mining from Big-Data
  • AIT 636 Interpretable Machine Learning
  • AIT 664 Information Representation, Processing and Visualization
  • AIT 726 Natural Language Processing with Deep Learning
  • AIT 736 Applied Machine Learning
  • AIT 746 Applied Deep Learning
• SEOR Elective Courses
  • OR 568 Applied Predictive Analytics
  • SYST 542 Decision Support Systems Engineering
  • SYST 573 Decision and Risk Analysis
  • SYST 584 Heterogeneous Data Fusion
• ECE Elective Courses
  • DFOR 510 Digital Forensics Analysis
  • DFOR 660 Network Forensics
• GBUS Elective Courses
  • GBUS 721 Marketing Research
  • GBUS 739 Advanced Data Mining for Business Analytics
  • GBUS 738 Data Mining for Business Analytics
  • GBUS 720 Marketing Analysis

Admission Requirements

Applicants must have completed a baccalaureate degree from a regionally accredited program with an earned GPA of 3.00 or better in their 60 highest-level credits. Applicants are expected to have completed a degree in engineering, business, computer science, statistics, mathematics, or information technology, with demonstrated foundational competence in calculus, statistics, and computer programming. Additional requirements include:

• Completed online application
• $75 application fee
• Undergrad GPA-minimum 3.0 (submit all undergraduate and graduate transcripts)
• GPA Addendum essay if undergrad GPA below 3.0
• 2 letters of recommendations
• Resume
• Detailed statement of career goals and professional aspirations
• Experience Grid
• Proof of English competency (if applicable)

Career Opportunities

The online MS in Data Analytics Engineering program combines strong foundational concepts with deep technical savvy and plenty of hands-on experience, allowing graduates to choose how they work with Big Data as they advance their careers. Graduates can work in various roles, including:

• Data architect/scientist
• Data engineer
• Data analyst
• Private, government, profit, and non-profit sectors
• Information-science-technology, systems engineering, and statistic industries

Tuition and Financial Aid

Tuition is $930 per credit hour, with an additional charge of $35 per credit hour for a distance education fee. Financial aid information is available through the Office of Student Financial Aid.

Accreditation

George Mason University is accredited by the Commission on Colleges of the Southern Association of Colleges and Schools to award bachelors, masters, and doctoral degrees.