Online MS in Applied Analytics Courses

Core Courses

Advanced Statistical Tools
This course introduces advanced statistical methods of building models for decision-makers, with a primary focus on modeling techniques such as logistic regression and discriminant analysis. Students will explore the application of statistical models through examples in business, finance, market research, and healthcare management.

Learning Outcomes:
Ability to use SPSS to solve problems and visualize data and apply statistical concepts and techniques to solve real-world business cases

Big Data Management
This course provides an understanding of the business value of big data, the importance of effective management of big data, and the development of technical competencies using leading-edge platforms for managing and manipulating structured and unstructured big data.

Learning Outcomes:
Ability to use data management platforms such as Hadoop and MySQL to store, retrieve, modify, and process data

Optimization Modeling
This course introduces the basic principles and techniques of applied mathematical modeling for managerial decision-making. The course emphasizes skills in model formulation, assumptions and limitations, and interpretation of results, with some discussion of mathematical theory. Students learn about models widely used in diverse industries and functional areas, including finance, operations, and marketing.

Learning Outcomes:
Ability to identify patterns in problem-solving, develop models based on organizational problems, identify solutions, test results, and effectively analyze and communicate findings

Predictive Analytics
This course teaches students critical skills for succeeding in today’s data-intensive world, including business case studies, data analysis, and management recommendations. Students learn how to utilize database systems and analytics software and how to make trustworthy predictions using traditional statistics and machine learning methods.

Learning Outcomes:
Ability to use tools like Python and SPSS to develop data-based predictions for businesses and organizations

Simulation Modeling
This course is designed to develop a student’s ability to model and analyze real systems using event simulation. It will apply computer modeling and simulation approaches for studying complex systems, with emphasis on using general-purpose programming tools. Areas covered include system structure, system analysis, model construction, data collection, and computer simulation.

Learning Outcomes:
Ability to collect data, formulate an appropriate simulation model for a system, implement the model as a computer program, and evaluate the output of the model

The Art and Science of Business Analytics
This course looks at creating organizational value through business analytics, which is the way in which enterprises such as businesses, nonprofits, and governments can use data to gain insights and make better decisions. Effectively using data to drive rapid, precise, and profitable decisions has been a critical strategic advantage for a lot of major companies.

Communications with Data
This course prepares students to communicate data insights, and it involves a combination of three key elements: data, visuals, and narrative. Students will get hands-on experience in collecting and organizing data in Tableau, and communicating a specific position or point of view from data through a combination of data-driven visuals and a carefully crafted storytelling technique.

Learning Outcomes:
Ability to use Tableau to collect data and translate it into a compelling and influential data story

Marketing Informatics
This course covers the use of information technology and systems that enable and enhance marketing strategies and tactics. This course prepares managers to face the challenges of various information systems, data collection methodology, and organization; the process of mining valuable information from the data; and ethical situations created by data collection and information use.

Programming for Business Analytics
This course introduces students to programming using Python, with a focus on learning how to develop algorithms. Current Topics (Python) will function primarily as a programming course, and students will practice applying their programming skills to analytics problems in examples, homework, and projects.

Learning Outcomes:
Ability to apply Python programming skills to solve analytical programs for businesses and organizations

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Elective Courses

Multiple Attribute Decision Analysis
This course examines a major class of problems in decision analysis: one-time decisions where a group of alternatives must be compared on the basis of multiple (and possibly competing) goals and objectives. Students will consider the social and environmental consequences of their firms’ actions, and how the ability to solve multi-attribute-decision problems has become more important than ever.

Learning Outcomes:
Ability to consider social, ethical, and environmental implications while making decisions, and choose a solution that will bring about the best possible outcome

Workflow and Business Process Modeling and Analysis
This course equips students with the knowledge and skills needed to analyze, evaluate, and model business processes. Students will also learn about designing business process improvements and solutions to increase business value and agility.

Learning Outcomes:
Ability to model, analyze, and evaluate business processes in an integrated, multidisciplinary way, and communicate techniques persuasively to encourage innovative business processes within an organization

Web and Social Media Analytics
This course focuses on the difference between knowing what stats mean and knowing which stats are meaningful. Students are first able to identify which metrics are important for decision making and focus on these rather than “vanity” metrics. This class also equips students to make critical decisions regarding trade-offs in terms of what is most important to decision makers.

Analytics for Customer Insights
This course covers the use of information technology and systems that enable and enhance marketing strategies and tactics. Various marketing systems are providing overwhelming amounts of data to marketers and other decision makers in organizations. In addition, this course prepares managers to face challenges that come with data collections and information use.

Valuation of Real Options
This course includes a review of the fundamental theory of decision analysis and options as well as an introduction to numerical techniques for solving dynamic programming problems, such as binomial lattices and trees. The course also provides hands-on experience with software tools used for the numerical analysis of problems using these ideas.

Supply Chain Analytics
This course focuses on a data-driven approach to supply chain management decision making. This class introduces and explains how analytics is being used by logistics and supply chain practitioners. Emphasis is placed on the development and use of analytics-based models to show the concepts in both intra-firm logistics and inter-firm logistics operations.

Healthcare Analytics
This course offers a comprehensive introduction to the fundamentals of healthcare research methodologies, including research design, data collection, and applied statistics. In addition, this course introduces students to basic operations research/management (OR/OM) techniques and demonstrates how those tools can also be applied in health service management.

Project Management
This course provides an introduction and an overview of the variety of topics and diverse functions of project management. The course explores the fundamental theory of each function and identifies essential project management skills, practices, and tools. Students are required to use skills learned throughout the course to implement a plan to deliver to a client, for a project.

Information Security Data Analytics
This course equips business managers to recognize and address the key risks to business information systems and data. Utilizing data analytics across different dimensions is critical for effectively providing information security analytics. An essential element of a risk-based approach is the use of user-behavior analytics (UBA) to compare and contrast threats against normal behavior.

Business Analytics and Intelligence
This course introduces techniques to transform data into business intelligence and to use analytics to create business value. Students learn to develop solutions to real-world problems through a combination of readings, case studies, applied projects, technology demonstrations, guest lectures, and assignments to analyze and interpret real data.

Competitive Intelligence
This course examines competitive intelligence (CI) models, functions, and practices; the roles of information professionals in CI; and the management of CI. Discussion and practice topics may include intelligence ethical and legal considerations and identifying intelligence needs and intelligence project management. Knowledge of print and electronic business information sources is recommended.

Financial Modeling
This course provides students with an understanding of financial decision making while creating financial models in spreadsheet packages such as Excel. Through a series of increasingly complex models, the class exposes the student to methodologies and practices that improve the student’s ability to communicate and present complex financial decisions.

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Earn your MS in Applied Analytics online from the Pepperdine Graziadio Business School in as few as 12 months.

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