As businesses and organizations increasingly turn to evidence-based decision-making, demand for professionals with data analysis and data wrangling skills is rapidly growing. According to a McKinsey Global Institute report, “the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.”

Available 100 percent online, Mercyhurst University’s four-course (12-credit) graduate certificate in Data Analytics offers an excellent introduction to this in-demand discipline, preparing students with the technical and analytical skills required for successful careers in data analysis and data wrangling. Notably, this program is open to individuals from every academic and professional background. An excellent introduction to an exciting discipline, this program offers instruction in the computer science skills necessary to learn data analytics; previous information technology or coding knowledge is not required.

Program Overview

  • Options: Graduate certificate
  • Location(s): Online
  • Credits: 12
  • Duration: Minimum 9 months
  • Cost: $1,026 per credit; $13,500 total
  • Deadline: Rolling admissions
  • Start term(s): Fall semester
  • Careers: Data analyst, business analyst, big data analyst

Mercyhurst University pioneered the field of intelligence studies in the mid-1990s and is home to the largest and oldest academic intelligence enterprise in the United States. Founded in 1996, the Ridge College of Intelligence Studies and Applied Sciences has earned a reputation throughout the world for the quality and cutting-edge analysis skills of its graduates. 

As “The Big Data Revolution” evolved, Mercyhurst has invested heavily in both data science and cyber security. Drawing on the diverse learning resources and experienced faculty of the Ridge College, these programs harness our national security bona fides to offer unparalleled instruction in some of today’s most dynamic fields. 

Learning Outcomes

Mercyhurst graduate programs are designed to give our students a competitive edge in the market place. You will be prepared as a professional data scientist who will serve as a key informant for decision-makers in both the public and private sectors. You will be able to:

  • Obtain, organize, and transform data into appropriate format for storage, exploration, visualization, and analysis
  • Store, analyze, and visualize big data on cloud computing platforms
  • Communicate analytic findings in easy-to-understand written, oral, visual, and/or multimedia formats to clients

Curriculum Requirements

Prospective students looking to earn a quick credential or ease into graduate school can opt for the four-course, 12-credit Graduate Certificate in Data Analytics. This program can be completed in as little as 9 months. Those credits can then be applied to the master’s degree in Data Science, should you choose to continue your education. Learn More

  • CIS 500: Computing & Information Science Concepts
  • CIS 501: Probability and Statistics
  • CIS 510: Algorithm Development
  • CIS 551: Big Data Analytics

CIS 500: Computing & Information Science Concepts

Computing & Information Science studies the design, application, use, impact and ethical implications of computational principles and technology. This foundational class prepares students for advanced courses in Data Sciences, Cyber Security, and Cyber Risk Management. Topics covered include: computer organization, data structures, computer programming, networking concepts, computer security, and ethics.

CIS 501: Probability and Statistics

This course provides an overview of concepts in probability and statistics including sampling distributions, normal theory estimation and hypothesis testing, regression and correlation, exploratory data analysis, logistic regression, discriminant analysis, resampling methods and linear model selection. Learning to perform statistical analysis on a personal computer is an integral part of the course.

CIS 510: Algorithm Development

This course reviews computer programming concepts and practice. Topics include: algorithms, abstract data types, linear and non-linear data structures, and software engineering. Students will get hands-on experience with the use of a high-level programming language to search and sort data.

CIS 551: Big Data Analytics

This course is an overview of Hadoop, MapReduce, and Hadoop Tools. Topics include: installing Hadoop (both on the desktop and in the cloud) and navigating the Hadoop Distributed File System, MapReduce and other essential Hadoop tools including Pig, Hive, Flume, Sqoop, and Hbase.

Career Paths

Data science is one of the most important disciplines of the future, and it will intersect with every professional area as the reservoir of the world’s data continues to grow. According to a McKinsey Global Institute report, “the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.”

Admissions Requirements

Prospective applicants for the graduate certificate in Data Analytics must fulfill the following admissions requirements. At the discretion of the director of the Data Analytics graduate program, acceptance may be granted to applicants who have not fulfilled all the admissions requirements provided they agree to the conditions of the acceptance prescribed by the director.

Admissions decisions are made by the program director on a rolling basis after a holistic review. Applicants can choose to start in either the Fall (preferred) or Spring semester.

  • Completed (free) online application
  • A bachelor’s degree in any discipline from an accredited school with a preferred overall minimum GPA of 3.0
  • Official transcripts from all post-secondary institutions you’ve attended 
  • A current resume 
  • A 500- to 750-word personal statement outlining your reasons for enrolling and personal and professional goals
  • International applicants whose records are written in a language other than English must have their documents translated into English and submit a notarized statement attesting to the accuracy of the translations
  • International applicants whose primary language is not English must attain a TOEFL score of at least 79 on the Internet-based exam OR an IELTS score of at least 6.5 OR a Duolingo English Test score of no less than 100.

Explore Financial Aid

Earn an affordable graduate certificate in data analytics with competitive per-credit costs. Visit our Graduate Cost and Financial Aid webpage or contact us at or 814-824-3351.

Contact Us

Christopher Mansour, Ph.D.
Chair, Department of Computing and Information Science
Office: Library 402
Phone: 814-824-2121

Colleen Hordych
Assistant Director, Graduate Admissions
Phone: 814-824-2297

Meet the Faculty

Computing and Information Science