With the rise of big data, there’s a real demand for specialized knowledge in data science. Understanding how to gather, analyze, interpret, and visualize data is a valuable skill in all disciplines.
Online Data Science Graduate Certificate
This graduate certificate is 100% online and designed to give you essential data analytics skills and enhance your value as an essential part of any team.
The Online Graduate Certificate in Data Science prepares you for the future of work, with essential knowledge and skills to solve real-world challenges in almost any business setting.
This 100% online graduate certificate program is designed for students holding a bachelor’s degree in any discipline and includes fundamental knowledge for those without a programming or data science background.
Coursework in this degree program covers:
- Computational and statistical foundations of data science
- Assumptions and limitations of different data analytics techniques
- Applying data science methodologies and tools to data-driven problems across disciplines
- Extracting knowledge from big data to address real-world challenges
- Retrieving, manipulating, analyzing, and visualizing data utilizing Python, R, and other data science tools
Careers to Pursue with a Graduate Certificate in Data Science
There is an industry need for data science-capable professionals, with job titles including
- Data Analyst
- Business Intelligence
- Developer
Upon completion, you will be prepared to apply data science in real-world in areas like:
- Business
- Engineering
- Education
- Defense and Security
- Natural Sciences
- Humanities
- Health Care
- Social Sciences
- and many others!
DS 5003. Intro to Data Science
An in-depth investigation into the Data Science life cycle. Focus areas on data visualization, data curation, tools available for data analysis, and software packages will be covered. Prerequisites: Any statistics course, or consent of instructor.
DS 5013. Programming for Data Science
An introduction to data-driven programming emphasizing problem solving, critical thinking, and algorithmic thinking. Topics will focus on foundational computer programming computer concepts along with fundamentals of object-oriented programming and math/statistics packages. Prerequisite: consent of instructor.
DS 5023. Data Organization and Visualization
This course investigates the data organization process from data integration to analysis and visualization through object-oriented design and implementation. Topics may also include data collection and sources, file input/output, data preprocessing algorithms, and data visualization using data science software packages and APIs. Prerequisite: DS 5003 and DS 5013.
DS 5033. Data Mining and Machine Learning
This course investigates fundamental data science concepts in in-depth analysis, data mining, machine learning, and artificial intelligence. Topics may include clustering, classification, evaluation metrics, supervised and unsupervised learning, search algorithms, intelligent agents, and advanced AI applications in select areas. Prerequisite: DS 5003 and DS 5013.
STA 6003. Statistical Methods in Research and in Practice
The course includes concepts and knowledge in basic probability, common distributions, point and interval statistical estimation, test of hypothesis, simple and multiple linear regression, and analysis of variance. Course emphasis will be placed on understanding the underlying assumptions and limitations of the different techniques. Prerequisite: One semester of calculus and one statistics course, or consent of instructor.
The prerequisites for this program are at least a bachelor’s degree in any discipline, including fine and liberal arts, business, education, engineering, health, humanity, technology, natural science, and social science. To maintain enrollment in the certificate program, students should maintain a 3.0 grade point average throughout tenure in the program.
| General University Requirements | Must meet certificate program regulations. |
| Application | A completed Graduate School application, unless currently enrolled as a degree-seeking graduate student. |
| Transcripts | Official transcripts from all institutions attended. All international transcripts must be recorded in English or officially translated to English. |
| Resume or Curriculum Vitae | Not required. |
| Letters of Recommendation | Nor required. |
| Statement of Purpose | Not required. |
| Test Scores | Not required. |
| Evaluation of Foreign Credentials | All applicants including non-U.S. citizens (International), U.S. Citizens, and permanent residents who have earned university-level credit from foreign institutions are required to submit official transcripts along with an evaluation of the transcripts from Foreign Credentials Service of America.
|
| International Applicants | Must meet international graduate student admission requirements
|
| Other | None. |
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