Program Description

Data analytics engineering has become an important activity for addressing Big Data and analytics required to solve problems and acquire valuable insights. The online Graduate certificate in Data Analytics engineering from George Mason University provides you with both knowledge and experience for working and solving real-world data analytics engineering problems. The certificate is a career enabler for students and working professionals that are interested in acquiring skills to expand the focus and scope of their current problem solving capabilities in the context of Big Data.

The certificate is based on four data analytics foundation courses and can be completed in roughly 12-months.  The foundation courses cover the key concepts and principals for practicing data analytics engineering roles of data engineering, data scientist, and data architect.

Concepts covered include:

  • Data, data quality, and large volumes of data
  • Data management and data mining
  • Modeling and model usage for making decisions
  • Statistical methods and visualization

If you decide to enroll in the online MS in Data Analytics Engineering degree at a later point, credits from the graduate certificate will apply.

Learn In a Top-Ranked School

George Mason’s Volgenau School of Engineering has worked with Big Data and cybersecurity for more than 25 years. It’s led by faculty with rich industry experience and connections who draw upon both to teach a proven, career-focused curriculum.

  • The 20 Best Schools to Study Big Data Analytics — TechRepublic, March 2016
  • Top 50 Best-Value, Big Data Graduate Programs — Value Colleges, 2018

Application Deadline

The online Graduate Certificate in Data Analytics Engineering program accepts applications on a rolling basis and is currently accepting applications. Applicants for the online program should apply here. Applicants for the on-campus program should apply here.

Virtual Open House

The George Mason University faculty dedicates time throughout the year to hold interactive sessions online for those who want to learn more about the programs we offer. If you would like to find out more about what you can expect from an online Graduate Certificate in Data Analytics Engineering, visit our pre-recorded Virtual Open House and watch at your convenience. For information on upcoming sessions, please don’t hesitate to contact us.

Request Info

Program Summary

100 Percent Online

Program: Data Analytics Engineering (MS)

Degree: Graduate Certificate

College/School: Volgenau School of Engineering

Credits: 12 total

Who should apply?

The certificate is intended for students who are interested in the challenges of transforming Big Data into meaningful information. While no specific undergraduate degree is required, a background in engineering, business, computer science, statistics, or information technology is desirable.

Why choose Mason?

  • No GRE/GMAT required.
  • George Mason’s Volgenau School of Engineering has worked with big data and cybersecurity for more than 25 years.
  • The program is top-ranked. It was named “The 20 Best Schools to Study Big Data Analytics” by the TechRepublic in March 2016 and one of the “Top 50 Best-Value, Big Data Graduate Programs” by Value Colleges in 2018.
  • World-renowned faculty with industry experience teach a career-focused curriculum that provides deep conceptual and practical knowledge.
  • 100% online format allows you to learn from the best when and where it’s best for you.

Program requirements for the online Graduate Certificate in Data Analytics Engineering program are subject to change.

Requirements: 12 total credit hours

  • OR 531 – Analytics and Decision Analysis
    • Course focus is predominantly on prescriptive analytics with some parts focused on predictive analytics. Topics include operations research techniques and their application to decision making such as mathematical optimization, networks modeling, stastistic modeling, and multi-objective modeling. Other topics such as PERT, CPM, computer simulation, decision analysis using decision trees and quantitative value functions, and heuristic methods are covered, as well as use of contemporary computer software for problem solving. In particular, the course will extensively use MS Excel for solving the decision-making problems. Case-study approach to problem solving is used.
  • CS 504 – Principles of Data Management and Mining
    • Techniques to store, manage, and use data including databases, relational model, schemas, queries, and transactions. On Line Transaction Processing, Data Warehousing, star schema, On Line Analytical Processing. MOLAP, HOLAP, and hybrid systems. Overview of Data Mining principles, models, supervised and unsupervised learning, pattern finding. Massively parallel architectures and Hadoop. Notes: This course cannot be taken for credit by students of the MS CS, MS ISA, MS SWE, CS PhD or IT PhD programs.
  • STAT 515 – Applied Statistics and Visualization for Analytics
    • Introduces multivariate regression and random forests for modeling data. Addresses data access, variable selection, and model diagnostics. Introduces foundations for visual thinking. Reviews common statistical graphics such as dot plots, box plots, q-q plots. Addresses more advanced methods such as scatterplot matrices enhanced by smoothed or density contours, and search tools for finding graphics with suggestive patterns. Notes: Course will introduce R software for analysis. A final project will involve visualization of a real data set.
  • AIT 580 – Big Data to Information
    • Course provides an overview of Big Data and its use in commercial, scientific, governmental, and other applications. Topics include technical and non-technical disciplines required to collect, process, and use enormous amounts of data available from numerous sources. Lectures cover system acquisition, law and policy, and ethical issues. It includes brief discussions of technologies involved in collecting, mining, analyzing, and using results.

Tuition & Fees (2020-2021):

Tuition is $930 per credit hour. An additional charge of $35 per credit hour applies for a distance education fee.

Financial Aid

For information on loans and scholarships, visit the Office of Student Financial Aid. For information regarding grants, tuition waivers and other merit aid, please inquire with your graduate department.

The online Graduate Certificate in Data Analytics Engineering program combines strong foundational concepts and technical savvy so you can produce actionable solutions from large data sets in your chosen field. As a data analyst, you’ll mine the systems that house Big Data and leverage them to produce actionable business strategies and solve problems.

You’ll find work in:

  • All sectors: private, government, profit, and non-profit
  • Information Science Technology, Systems Engineering, and Statistic industries

Data Scientist vs. Data Analyst Titles

Though the titles can often share or overlap responsibilities, and are sometimes used to mean the same thing, in the strictest definitions, data scientists and data analysts are different roles. Mason’s online Graduate Certificate in Data Analytics Engineering prepares you for both.

  • Data Scientists design the systems for handling data. They have a strong background in computer science and experience in building systems.
  • Data Analysts are generally subject matter experts. They have input into the systems that are designed, but their job is to mine the systems and leverage them to produce actionable strategy.

If you are unable to find the answers to your questions, submit a Request For Information form or contact our admissions representative via the contact information below.

Phone: 703-348-5006
Email: online2@gmu.edu

How do I apply?

Applicants for the online program should apply here.

ADMISSIONS FAQs

Can I take courses without applying?

Only students who are admitted to the Data Analytics Engineering Certificate program may take classes in the program.

What are the requirements for admission?

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. Applicants without that formal academic preparation but with clear evidence of strong and extensive work experience in data or analytics, may also be considered on a case by case basis.

In addition to fulfilling Mason’s admission requirements, applicants must provide:

  • Completed online application
  • $75 application fee
  • All undergraduate and graduate transcripts (undergrad GPA-minimum 3.0)
  • GPA addendum essay if undergrad GPA below 3.0
  • Two letters of recommendation, preferably from academic references or references in industry or government who are familiar with the applicant’s professional or academic accomplishments
  • Resume
  • Detailed statement of career goals and professional aspirations
  • Completed self-evaluation form
  • If the applicant’s native language is not English, proof of English competency with a minimum TOEFL score of 575 for the paper-based exam or 230 for the computer-based exam

How long does it take to complete the program?

The online Data Analytics Engineering Certificate is 12 credit hours and can be completed in roughly 1 year, or as little as 10 months.

When are classes held?

Online classes are offered in an asynchronous format, meaning they can be viewed interactively at your convenience. However, students still must meet all study and deliverable requirements and deadlines.

What accreditation does George Mason hold?

George Mason University is accredited by the Commission on Colleges of the Southern Association of Colleges and Schools to award bachelor’s, master’s, and doctoral degrees.

How much does it cost to apply?

While there is a $75 application fee, there are multiple times throughout the year that it may be waived.