The field of data analytics is a very vibrant and broad field. The amount of data available and computing power have exploded in recent years. There is an increasing demand for business analysts who can select and apply the appropriate methods and interpret the results within the context of the problem. The goal of this course is to learn methods for exploring data and building models with the purpose of supporting data-driven decision making. The content of the course can be grouped as follows: Data Exploration, Probability, Confidence Interval Estimation, Hypothesis Testing and Regression Analysis. The focus will be on exploring realistic business scenarios, analyzing datasets using the appropriate analytical techniques, interpreting the analytic output within the context of the business scenario and translating the statistical results into actionable insights.

The fundamentals of managing data and information within an organization, including enterprise level platforms and tools for data driven analytics. Includes processes for acquiring and cleaning data, storing data, making it available for analytics, visualizing output, and archiving the data for long term use. Involves computational thinking, covers significant theoretical material on data models and queries, and teaches several different analytics and programming tools.

Difficult decisions require spending scarce resources. A 'resource' is any asset used to leverage business objectives, such as time and money. Tradeoffs are involved in allocating resources to one objective as opposed to another. This course develops a quantitative framework for studying resource allocation problems that arise in many industries and areas such as transportation, advertising, finance, and healthcare. The focus will be on translating verbal descriptions into quantitative optimization models, whereby standard tools (such as Microsoft Excel) can be applied to obtain solutions. The course also covers the role of uncertainty and risk in the decision-making process by using Monte-Carlo simulation models.

The fundamental question that this course addresses is "why are some firms more successful and more profitable than others?" This is both a static and dynamic question, in that we can ask why a given firm is competitively stronger and more profitable at a moment in time, as well as how a firm can sustain competitive advantage and grow profitably over a period of time. This course aims to give you the tools, frameworks, and ideas necessary to develop business strategies, both in the short and the long run. We focus on how best to analyze the structure and dynamics of the external industry environment; how best to analyze and identify a firm's valuable assets, resources and capabilities and how they might be protected, leveraged, and extended in the market; how to respond to environment changes; and how to design strategies for profitable growth and diversification over time.

In this short course we will study managerial economics at the firm level through the lens of a global company. We will mix classic theory, drawn from renowned experts and case studies, then also put those theories to the test through a competitive online and interactive simulation set within the pharmacology industry. The course will focus on understanding critical aspects of economics that influence firm decisions and behavior. This includes basic microeconomic principles used by firms, including supply and demand, elasticities, costs, productivity, pricing, market structure and the competitive implications of alternative market structures, market failures, and government intervention. Throughout the course we will also discuss public policy processes affecting business operations.

Overview of financial accounting, periodic financial statements and the financial reporting process. Importance of financial statements as information source for creditors and investors and as a means by which managers can communicate information about their firms.

The intent of this course is to provide students with an overall understanding of the fundamentals of supply chain analytics. Students will be introduced to analytical models and techniques that underlie modern supply chain planning and control systems. The primary supply chain activities of interest will be inventory and transportation.

This course aims to provide useful diagnostic tools, intervention strategies, and change models to understand and manage organizational change and its core processes, as well as critical knowledge and skills to initiate and facilitate an organizational change as effective change agent.

Information technology has enabled the transformation of firms, markets, and industries. Amazon is in the process of transforming the publishing industry and has been highly disruptive for booksellers and increasingly for publishers. The digital camera transformed the process of capturing and sharing images. Kodak invented the digital camera, but how did the managers at Kodak respond to digital photography? What is the smartphone doing to low-end digital camera manufacturers? This course examines how to identify transformational technologies and develop strategies to take advantage of them through a set of videos, readings, individual, and team assignments.