Applied Business Analytics Graduate Certificate
Available online and on campus, the Graduate Certificate in Applied Business Analytics provides comprehensive coverage of data analytics concepts, techniques, and state-of-the-art tools used in the process of data-driven business decision-making. Students have the opportunity to gain hands-on experience with a variety of analytical models and decision-support tools and to apply them to interlinked data-inputs and large data sets in the areas of marketing, operations, product and technology innovations, financial services, human resources management, and others. The curriculum covers advanced software tools and functions such as predictive modeling, text and data mining, visual analytics, simulations, and OLAP tables. Graduates of the program will be able to analyze data-driven business processes, select appropriate analytical methods to monitor and identify performance issues, and propose optimal data-based solutions.
Students who complete the Graduate Certificate in Applied Business Analytics will be able to demonstrate:
- The knowledge and skills to better utilize available information in operational, tactical, and strategic decision making in organizations.
- The ability to apply various powerful emerging technologies and techniques for increasing the value of both in-house and third-party data sets.
- An understanding of how organizations are using interlinked data-inputs, analytics models, and decision-support tools to better understand their operations, customers, and markets.
- The skills to understand web analytics and metrics, procure and process unstructured text, and delve into their hidden patterns.
- The expertise to facilitate knowledge discovery using data mining and visualization techniques over vast amounts of data.
Graduate Certificate in Applied Business Analytics Program Options
Available on campus and in the following formats:
Prior to starting a certificate program, students are required to submit a graduate application and an official transcript conferring a bachelor’s degree from a regionally accredited institution (or the international equivalent). Students must be admitted into a certificate program prior to taking courses, in order for those courses to be credited toward the certificate.
For application materials, visit the MET Admissions page.
A 3.0 GPA is required for certificate award, and no course with a grade below B- may be credited toward the certificate. Individuals considering using graduate certificate courses toward the master’s in Administrative Studies (MSAS) or master’s in Applied Business Analytics (MSABA) must:
- Apply to the MSAS or MSABA degree program prior to completing two courses
- Recognize that grades earned in certificate courses will not be used in the admission decision process
- Meet the department’s academic admission requirements
As a prerequisite to the course MET AD 571 Business Analytics Foundations, applicants are required to complete MET AD 100 Pre-Analytics Laboratory. MET AD 571 is a prerequisite for MET AD 616, MET AD 654, MET AD 688, and MET AD 699. Some courses may have additional prerequisites.
(Four courses/16 credits)
MET AD 571 Business Analytics Foundations
Prereq: AD100 Pre-Analytics Laboratory
This course presents fundamental knowledge and skills for applying business analytics to managerial decision-making in corporate environments. Topics include descriptive analytics (techniques for categorizing, characterizing, consolidation, and classifying data for conversion into useful information for the purposes of understanding and analyzing business performance), predictive analytics (techniques for detection of hidden patterns in large quantities of data to segment and group data into coherent sets in order to predict behavior and trends), prescriptive analytics (techniques for identification of best alternatives for maximizing or minimizing business objectives). Students will learn how to use data effectively to drive rapid, precise, and profitable analytics-based decisions. The framework of using interlinked data-inputs, analytics models, and decision-support tools will be applied within a proprietary business analytics shell and demonstrated with examples from different functional areas of the enterprise. [ 4 cr. ]
|A1||IND||Ritt||CAS 326||M||2:30 pm – 5:15 pm|
|A2||IND||Staff||CAS 237||M||6:00 pm – 8:45 pm|
|A4||IND||Ritt||KCB 106||W||2:30 pm – 5:15 pm|
|A5||IND||Staff||CAS 237||W||6:00 pm – 8:45 pm|
|A6||IND||Staff||KCB 103||W||6:00 pm – 8:45 pm|
Plus three chosen from the following:
MET AD 616 Enterprise Risk Analytics
The course offers an overview of the key current and emerging enterprise risk analytical approaches used by corporations and governmental institutions and is focused on understanding and implementing the enterprise risk management framework on how to leverage the opportunities around a firm to increase firm value. The major risk categories of the enterprise risk management such as financial risk, strategic risk and operational risk will be discussed and risk analytics approaches for each of these risks will be covered. Students will learn how to use interlinked data-inputs, analytics models, business statistics, optimization techniques, simulation, and decision-support tools. An integrated enterprise risk analytics approach will be demonstrated with examples from different functional areas of the enterprise. [ 4 cr. ]
|A1||IND||Staff||CAS 233||M||6:00 pm – 8:45 pm|
|A2||IND||Staff||MET 122||T||12:30 pm – 3:15 pm|
MET AD 654 Marketing Analytics
Become familiar with the foundations of modern marketing analytics and develop your ability to select, apply, and interpret readily available data on customer purchase behavior, new customer acquisition, current customer retention, and marketing mix optimization. This course explores approaches and techniques to support the managerial decision-making process and skills in using state-of-the-art statistical and analytics tools. Students will have an opportunity to gain basic understanding of how transaction and descriptive data are used to construct customer segmentation schemas, build and calibrate predictive models, and quantify the incremental impact of specific marketing actions. [ 4 cr. ]
|A1||IND||Staff||CAS 426||W||6:00 pm – 8:45 pm|
|A2||IND||Shapiro||CAS 213||W||2:30 pm – 5:15 pm|
MET AD 688 Web Analytics for Business
Explore web analytics, text mining, web mining, and practical application domains. The web analytics part of the course studies the metrics of websites, their content, user behavior, and reporting. The Google analytics tool is used for collection of website data and doing the analysis. The text mining module covers the analysis of text including content extraction, string matching, clustering, classification, and recommendation systems. The web mining module presents how web crawlers process and index the content of web sites, how search works, and how results are ranked. Application areas mining the social web and game metrics will be extensively investigated. [ 4 cr. ]
|A1||IND||Staff||CAS 315||M||6:00 pm – 8:45 pm|
|A2||IND||Staff||CAS 213||T||6:00 pm – 8:45 pm|
MET AD 699 Data Mining for Business Analytics
Enterprises, organizations and individuals are creating, collecting, and using massive amount of structured and unstructured data with the goal to convert the information into knowledge, to improve the quality and the efficiency of their decision-making process, and to better position themselves to the highly competitive marketplace. Data mining is the process of finding, extracting, visualizing and reporting useful information and insights from both small and large datasets with the help of sophisticated data analysis methods. It is part of the business analytics, which refers to the process of leveraging different forms of analytical techniques to achieve desired business outcomes through requiring business relevancy, actionable insight, performance management, and value management. The students in this course will study the fundamental principles and techniques of data mining. They will learn how to apply advanced models and software applications for data mining. Finally, students will learn how to examine the overall business process of an organization or a project with the goal to understand (i) the business context where hidden internal and external value is to be identified and captured, and (ii) exactly what the selected data mining method does. [ 4 cr. ]Fall 2020
|A1||IND||Staff||CAS 315||T||6:00 pm – 8:45 pm|
|A2||IND||Staff||SOC B57||T||12:30 pm – 3:15 pm|
View all Analytics courses.