Predictive analytics is a highly statistical field, where historical data is analyzed in order to predict what may happen in the future. Graduate certificate programs that focus on predictive analytics may be dedicated solely to the topic or may be incorporated into a wider certificate in data analytics. Given that the course topics usually include data and statistics, these graduate certificate programs can be useful for professionals who are working in careers related to business intelligence, web analytics, and marketing.
Typical Courses in Graduate Certificate Programs in Predictive Analytics
Graduate certificate programs in predictive analytics may have between 12 and 16 credit hours' worth of course materials that students can complete online or in person. In some cases, the credit from the courses in the program can be transferred to a master's degree in a similar area.
These kinds of courses may introduce students to the methods and technologies that are used in business intelligence. In some of these courses, students may have to complete a project that includes a business intelligence plan. Other topics that may be covered include data warehousing, how to make business decisions based on data and data staging.
Predictive analytics courses should begin by providing students with a basic understanding of what predictive analytics is and how it can be applied to businesses and helping to improve performance. These courses can be hands-on in nature and will allow students to explore important concepts in extracting stored data. Students can expect to delve deeper into the storage and extraction of data, how to manipulate it and present it in different ways using visualization techniques.
R programming is a scripting tool used for analyzing data and manipulating statistical data and is a key part of predictive analytics. When students are enrolled in these courses, they may learn about the basics of using this scripting language and programming and exploring how to use this functionality to help solve statistical and mathematical business problems. Students will delve deeply into math problems and concepts in this course.
Courses of this nature are designed to introduce students to the basics of predictive modeling and how they can be used. Some of the topics that may be covered in these courses are deployment strategies, source code, and modeling software. In some courses, students may gain 'hands-on' experience through the use of projects.
Data-based courses explore how data is extracted through data mining, processed and prepared so that it can be presented in appropriate formats. These courses are hands-on and will allow students to practice mine data, learn how to understand it and use visualization techniques to present data to businesses in suitable formats. Students will learn how to use this data to then help with future predictive analysis.
General Admission Requirements for Graduate Certificate Programs in Predictive Analytics
Prospective students may need an undergraduate degree from an accredited college or university. These programs may not require a specific subject area for the undergraduate degree but some need the applicant to have a minimum GPA of 2.7. Along with an application, students may be required to submit school transcripts, letters of recommendation, a current resume and a personal essay. Some programs may also require passing scores on the GRE or GMAT exams.
A graduate certificate program in predictive analytics may also be included as part of a wider data analytics certificate, but even so, there are some core courses that students can expect to cover. These programs can help professionals in analytical fields enhance their knowledge and skills as long as they have an undergraduate degree from an accredited college or university.