Advanced Certificate in Business Analytics Courses

Develop Your Analytics Skills Online or On-campus

All courses taken in the certificate program are graduate-level Information Systems courses and may be applied to Marist's Master of Science in Information Systems (MSIS) program, provided the grades earned are B or better. However, because of the more comprehensive nature of the MSIS program, admission requirements are more rigorous and additional technical competency may be gained through taking some prerequisite courses. Specific requirements would be identified when admission to the MSIS program is requested.

Format:

• Students generally carry two courses per semester, and take one year to complete the certificate.
• Courses are offered 100% online without residency or on-site at our main campus in Poughkeepsie, NY.

Business Analytics Course Descriptions

The Advanced Certificate in Business Analytics is obtained upon satisfactory completion of the following four courses (12 credits):

MSIS 537 Data Management I 3 credits
A study of the critical issues related to managing data in organizations. The concept of data as a resource, the data environment, the database approach, and the need for data modeling are examined in detail. The growing use of database management systems in managing data is discussed. The data administration function, its relevance in evolving organizations, and emerging issues are also addressed.

MSIS 545 Introduction to Data Analysis & Computational Statistics 3 credits
This is an introductory course in data analysis with emphasis on statistical computation, analysis, simulation, modeling and prediction. A basic presentation of modern computational data analysis, graphics and inferential statistics is provided in a laboratory setting; students gain proficiency in using a statistical software platform such as R. The course will cover probability concepts, important distributions, descriptive statistics and graphical analysis, inferential statistics including confidence intervals, hypotheses testing and ANOVA, as well as correlation and linear regression in one and several covariates. Computational techniques such as the bootstrap and re-sampling as well as for simulations are stressed throughout. Principles and methods of statistical analysis are put into practice using a range of real-world data.

MSIS 637 Decision Support Systems 3 credits
This course covers concepts and tools that aid managerial decision making by applying analytic reasoning and computer-based tools to managerial problems. Managers are increasingly overwhelmed by the speed of decision making, the number of decisions, and the amount of data available to help make these decisions. Their success depends on their ability to extract business value from the raw data their organization collects. The course focuses on decision making techniques and tools including such topics as management science, model-driven decision support, data-driven DSS, expert systems, and business intelligence.

MSIS 645 Data Mining & Predictive Analytics 3 credits
Data Mining & Predictive Analytics is the name given to a group of disciplines, technologies, applications and practices for analyzing data (usually based on past business performance) and building models to help enterprise users make better, faster business decisions. The course covers basic concepts, tasks, methods, and techniques in data mining, including data exploration, data preparation, classification, regression, clustering, association, and performance evaluation applied to predictive modeling.

Prerequisite: While there are no official pre-requisites for this course, it is expected that all students are familiar with elementary probability and statistics (recommended: MSIS 545). 

 

 

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