A Graduate Certificate is available for students wanting to further their education.
Data science continues to be in high demand and the skills for data practitioners
are needed in every industry. The Graduate Certificate in Data Science at MTSU allows
everyone the opportunity to learn the data skills needed to compete in the current
and future marketplace.
Students will learn how to solve data related problems by understanding the data,
exploring and cleaning the data, then visualizing the data to create and optimize
predictive models. Skills learned include:
- A business-driven approach to problem solving with data.
- The foundational statistical knowledge needed to understand and manipulate data.
- Programming skills to clean, transform, explore, visualize, and build models with
data using Python and its relevant libraries.
- Necessary skills to tune and optimize models for production, so that you not use data,
but you make it actionable.
A Master’s degree is in development.
For more information email firstname.lastname@example.org.
First student calls Data Science program 'too cool to pass up'
As the first student accepted into the Data Science Certificate program, Alex Dunn
admits he’s never been one to make long-term plans, or think he'd wind up in grad
school. After hearing more and more about the value of data science over the last
few years, and doing research into the career path, he discovered data scientist is
ranked first in job satisfaction both financially and spiritually.
“I’m looking for room to grow in my career, and data science checks that box for me.
I plan to continue into a masters, and possibly a Ph.D. This program is just perfect
for me right now,” he said. After he completes the certificate program in the Spring
of 2021, Alex said he hopes to take on more projects at his current company, or even
move into a full-time data science role. “Who knows,” he said. “This program is just
too cool to pass up.”
MTSU receives Nashville Technology Council awards
Middle Tennessee State University represented well at the 2020 Nashville Technology
Council Awards, bringing home three of the major awards for the evening, “Data Scientist
of the Year,” “Technology Student of the Year,” and “Diversity and Inclusion Initiative
of the Year.” These are incredible accomplishments that prove that MTSU’s efforts
in promoting education in data science are preparing students to make valuable contributions
in the rapidly growing Nashville technology community. The Nashville Technology Council
has worked as a hub for bringing technology companies together and recognizing industry
leaders. As a $7.5 billion-dollar industry that continues to flourish, the demand
for information technology jobs will continue to grow, and MTSU has industry-leading
resources, expert faculty, and driven students that will make an impact for years
MTSU True Blue Preview | Data Science
The Tennessee Digital Agriculture Center is Helping Farmers with Data and Drones
Students Create Innovative Technologies at the 2022 'HackMT' Event
AWS DeepRacer | Amazon Web Services and MTSU Data Science Race Machine Learning Remote Cars
This degree is intended to help individuals be more competitive in their current role
or allow them to pivot into a new career path. Below are different careers and companies
for this Graduate Certificate.
Careers directly related to this certificate
- Business Analyst
- Business Intelligence Analyst
- Data Analyst
- Data Analytics Consultant
- Data Architect
- Data Engineer
- Data Infrastructure Engineer
- Data Mining Engineer
- Database Administrator
- Junior Data Scientist
- Machine Learning Engineer
- Marketing Analyst
- Operations Analyst
- Quantitative Analyst
- Software Developer
- Systems Analyst
Career path with experience or additional education
- AI Engineer
- Data Scientist
- Quantitative Researcher
Notable Companies looking to hiring in Data Science:
- Bank of New York Mellon
- CAT Financial
- Change Healthcare
- Digital Reasoning
- Dollar General
- EFC Systems
- Hospital Corporation of America (HCA)
- HPA Cognizant Technologies
- Ingram Content Group
- Juice analytics
- State of Tennessee
- The General
- Tractor Supply
- Vanderbilt Medical
MTSU offers a graduate certificate in Data Science. This includes the four courses
listed below. These are mostly online courses. Each course is 7 weeks long and the
certificate can be completed in two semesters.
- DATA - 6300 - Data Understanding
- DATA - 6310 - Data Exploration
- DATA - 6320 - Predictive Modeling
- DATA - 6330 - Model Optimization and Deployment
For complete curriculum details, click on the REQUIREMENTS button to the right.
For more information about Data Science at MTSU, please contact Data Science at email@example.com.
Data Science Certificate
Qiang Wu, Program Director
The curriculum of the certificate program in Data Science is designed to provide students a realistic idea of the work of a data scientist. After successful completion of an introductory course, students will work with predictive modeling and data exploration. Program is designed for completion within two semesters.
Admission to the Data Science certificate program requires
- an earned bachelor's degree from an accredited university or college;
- an acceptable grade point average in all college work taken.
All application materials are to be submitted to the College of Graduate Studies.
- submit application with the appropriate application fee (online at www.mtsu.edu/graduate/apply.php). Once this initial application has been accepted, the applicant will receive directions on how to enter the graduate portal to be able to submit other materials. NOTE: When applying please choose "Data Science Graduate Certificate" instead of "Non-Degree Seeker."
- submit official transcripts of all previous college work.
Application deadline is July 31 for those wishing to begin the following Fall and December 31 for those wishing to begin the following Spring.
Candidate must maintain a cumulative grade point average of 3.0 in courses leading to the certificate.
Curriculum: Data Science
Required Courses (12 hours)
DATA 6300 - Data Understanding
Applications used to understand the problem-solving process for data science. Data collection and cleansing techniques used to visualize and summarize the data in order to prepare it for modeling for various data types through statistical analysis with Python programming.
DATA 6310 - Data Exploration
Prerequisite: DATA 6300. Data science techniques to explore numerical and text data. Unsupervised learning and NLP applications used to explore data to understand its impact and use to make data-driven decisions.
DATA 6320 - Predictive Modeling
Prerequisite: DATA 6300. Develop models to predict outcomes through the use of supervised learning techniques. Applications in regression and classification modeling used to develop data driven problem solving to predict and support decisions and analysis.
DATA 6330 - Model Optimization and Deployment
Prerequisites: DATA 6310 and DATA 6320. The optimization and deployment of machine learning models. Techniques for fine-tuning parameters for developing the best model for the presented business problems. Applications through internal and cloud infrastructures also used to identify optimal techniques for deployment of models to operationalize into production.
Our adjunct faculty bring outstanding professional experience to our programs. Many are industry leaders with decorated careers and honors. Importantly, they are innovative educators who offer hands-on learning to our students to prepare them to enter and thrive in a dynamic, and oftentimes emerging, industry and professional world. They inspire, instruct, and challenge our students toward academic and professional success.
Students in Data Science programs at MTSU have the added opportunity to work with
faculty from across the university on research and data contracts. Through the Data Science Institute, the following types of projects are possible:
- Data projects that help nonprofits. An opportunity to sharpen skills and use data
- Data projects with companies. These can be compensated opportunities for students
to work on real projects for businesses that need help analyzing their data.
- Data Dives (hackathons), which are events that allow all students to participate in
a hackathon style event where data from a nonprofit or company is presented and then
students have 24 to 36 hours to analyze the data to solve specific objectives.
- Research projects with faculty. Either funded or unfunded research that is data-driven
in any discipline.