Master of Science in Applied Analytics
The M.S. in Applied Analytics is a 30-credit, fully online program designed for professionals who are interested in enhancing their knowledge and skills within the field of data science and applied analytics. The program dives into the core concepts and principles of data analytics, providing a solid foundation in statistical methods, artificial intelligence, and machine learning to understand, analyze, and interpret massive amounts of data. Throughout the program, students will not only acquire theoretical knowledge in the field but also develop and improve essential skills in critical thinking and problem-solving, leadership, managerial communication, teamwork and collaboration, and ethical decision-making.
Program Learning Objectives
This program provides students with the essential skills required in the field of applied analytics. Upon successful completion of this program, graduates should be able to:
- Leadership: Evaluate large stores of data as part of database design to discover patterns and trends that go beyond simple analysis to new and industry-leading insights.
- Problem Solving & Critical Thinking: Apply analytic tools such as machine learning and artificial intelligence to critically evaluate applied research and develop meaningful insights.
- Disciplinary Knowledge: Analyze descriptive and inferential statistics and interpret the computer-generated statistical results with data visualization in business applications using programming languages such as R and Python.
- Ethical Reasoning: Develop ethical decision-making competencies through statistical methods and the application of analytical tools such as Microsoft Power BI.
- Strategic Thinking: Strategize how the issues facing leaders and decision makers, in a variety of fields, can be resolved ethically.
- Managerial Communication: Analyze and present big data to make strategic decisions including resource allocation. Bridge the communication gap between technical and traditional business managers.
- Teamwork: Collaborate and contribute effectively to the achievement of organizational goals in a team environment.
Program design
This 30-credit hour program is delivered through online instruction, providing flexibility and convenience for working professionals and adult learners. The program is designed with six core courses, three concentration courses, and the experiential capstone course. The six core courses will enhance students’ mathematical and technology skills. This core curriculum is supplemented by three concentration courses in decision-making and management, in which students will apply the skills learned in the core courses to their concentration of choice: management or education. The experiential learning capstone allows students to apply their skills in a real-world setting.
The program may be completed in as little as 15 months through full-time enrollment (typically 9 credits in fall and spring terms, 3-6 credits in summer terms). Part-time students may complete the program in two years. All students must complete the degree within six years of initial enrollment per the Graduate Time Limit for Program Completion Policy.
Prerequisites
In addition to a bachelor’s degree from a regionally accredited college/university, applicants must have undergraduate-level or graduate-level coursework in statistics (3 credits) and information technology (3 credits) to be considered for admission. Students who are missing one or both prerequisites, but are otherwise qualified and accepted into the program, will be required to take the missing prerequisites before starting the core classes.
Core Courses (18 Credits)
The courses below are required for both concentrations.
- INFT 6015 Database Design and Management (3 credits)
- APAN 6015 Data Models and Structured Analysis (3 credits)
- APAN 6010 Computer Aided Multivariate Analytics (3 credits)
- APAN 6020 Data Mining & Machine Learning for AI (3 credits)
- MGMT 6095 E-Commerce Marketing Strategies (3 credits)
- MGMT 6185 Quantitative Methods for Decision Making (3 credits)
Concentration Courses (9 Credits)
Students must take the courses from one of the following concentrations that they declared upon admission.
Management
- PPOL 6020 Research Methods (3 credits)
- MGMT 6105 Leadership in Public and Nonprofit Organizations (3 credits) OR MGMT 6040 High Performance Management (3 credits)
- APAN 6025 Applied Management Analytics (3 credits)
Education
- PPOL 6020 Research Methods (3 credits)
- CURI 6015 Leading in a Learning Environment (3 credits)
- EDET 6080 Evaluation, Assessment, and Data-Driven Learning Design (3 credits)
Capstone Practicum (3 credits)
- APAN 7010- Applied Analytics Capstone (3 credits)
The capstone will provide students with the ability to apply concepts in applied analytics to real-world situations. Students can select their capstone project from one of the following options:
- Employer-based Project: Work on a data analytics project with their current employer that demonstrates mastery of the capstone learning outcomes.
- Self-Selected Specialization Project: Choose a project based on their specialization and personal interest. This should involve real-world data and be geared toward deriving real-world insights.
For more information about this program, its course sequencing and descriptions, please visit the Empire State University's Academic Catalog.