Certificate Requirements

The Upper Division Certificate in Data Analytics is open to any undergraduate major at Bowie State University with CGPA 2.0 or above. The program is also open to individuals who have completed a bachelor's degree. The certificate requirements are successful completion of the following four courses:

• BUIS 362 Database for Business (**Prereq. BUIS 260 or equivalent) (3): This course provides an understanding of how data resources can be managed to support decision-making within organizations.  It will examine the use, development, and implementation of organizational databases and how the database environment is used to support decision-making.  Database design and implementation issues will be addressed from both a logical and physical perspective.  In addition, strategic and administrative issues of databases will be considered. This course is offered in Fall and Spring semesters.
  
  **Note that the pre-requisite BUIS 260 Computer Applications for business course or equivalent courses offered in the CTEC or Computer Science Departments (3) is taken by all students to. This can satisfy the general education requirements for Technology. This course is offered in Fall, Winter, Spring and Summer semesters.
• DANL 340 Visualization and Visual Analytics (**Prereq. DANL 280 or equivalent; and a statistics class) (3): This course focuses on descriptive analytics and covers design principles, methods, techniques and tools for visualization of data, information and/or knowledge from various sources and in various domain areas including natural sciences, information systems, cybersecurity, businesses and social sciences. The course also covers visual analytics techniques, tools and their applications. This course is offered in Spring semester.
  
  **Note that the pre-requisite  DANL 280 Foundations of Data Sciences and Analytics (Prereq. BUIS 260 or equivalent) (3) can be used to satisfy a general education elective or free elective requirement. This     course is offered in Fall, Winter, Spring and Summer semesters.
• BUIS 462 Decision Science and Analytics (Prereq. BUIS 362 or equivalent) (3): First the course provides foundation knowledge on decision making process and decision science. Then the course focuses on Predicative Analytics and covers the data mining (DM) processes for discovering patterns from both structured and unstructured data, and machine learning (ML) approaches, techniques, algorithms and their applications. It focuses on the applications of DM and ML for scientific and business problem solving using Machine Learning Software and/or Machine Learning libraries available in Python, R or other programming languages. This course is offered in Spring semester.
• DANL 480 Big Data Analytics (Prereq. BUIS 462) (3): The course provides in depth coverage of the methods, tools, and applications used to extract and analyze big data with a focus on solving real world problems such as uncover hidden patterns, correlations and other insightful relationships. This course covers the technologies and tools used to store, retrieve and process big data. Other topics covered in the courses are text analytics, sentiment analysis, text mining, web analytics, streaming or real-time data analytics, network analytics, temporal and geospatial data analytics. This course is offered in Fall semester.