Round out your Full-Time MBA degree with the quant skills employers are seeking.

COURSE CODE: is823

This Level 2 (non-programming-based) analytics course examines how the abundance of data has transformed decision making in organizations and the strategic implications of this transformation. We explore how data are being used, ranging from the core principles of properly identifying data sources to the actual analytical methods being used to solve a wide range of business problems. Students will have some hands-on work with advanced Excel, Tableau, and two database applications, Microsoft Access and Neo4j (Neo4j is used to compare and contrast SQL and NoSQL databases in an analytics context). At the end of this course, students will have gained a big-picture perspective on business analytics as well as hands-on experience with commonly-used business analytics software.

COURSE CODE: is833

This course will introduce students to programming-based tools and techniques for becoming analytically-minded managers. The course covers both a hands-on introduction to the concepts, methods and processes of business analytics as well as an introduction to the use of analytics as the basis for creating a competitive advantage. We will review variables, data types, conditionals, loops, and functions, and use these to introduce data structures, including DataFrames. We will also cover reading and writing raw files and the core APIs in analysis and visualization. With the basics under our belt, we will complement it with some of the most popular libraries for data analysis in Python, such as Pandas and Numpy for data manipulation, Matplotlib and Seaborn for visualization, and Jupyter Notebook for reporting. These packages will facilitate workflow and enhance the basic Python functionalities. Using them, one can effortlessly clean up a dataset, create elaborate plots, analyze and summarize the data, and produce presentable reports. Throughout the final project, we will learn to extract value from data by asking the right questions and using the appropriate analytical methods and tools. These methods comprise data preprocessing, explanatory analysis, and machine learning techniques. Prior programming experience in Python is required.

COURSE CODE: is834

This course will introduce students to programming-based tools and techniques for becoming analytically-minded managers. The course covers both a hands-on introduction to the concepts, methods and processes of business analytics as well as an introduction to the use of analytics as the basis for creating a competitive advantage. We will cover variables, data types and data structures, DataFrames, conditionals, loops, and functions. We will also cover reading and writing raw files and the core APIs in analysis and visualization. With the basics under our belt, we will complement it with some of the most popular libraries for data analysis in Python, such as Pandas and Numpy for data manipulation, Matplotlib and Seaborn for visualization, and Jupyter Notebook for reporting. These packages will facilitate workflow and enhance the basic Python functionalities. Using them, one can effortlessly clean up a dataset, create elaborate plots, analyze and summarize the data, and produce presentable reports. Throughout the final project, we will learn to extract value from data by asking the right questions and using the appropriate analytical methods and tools. These methods comprise data preprocessing, explanatory analysis, and machine learning techniques. No prior programming experience is required. Learning basic programming in Python is part of successfully completing the class.

COURSE CODE: qm870

This course teaches students the core elements of the R programming language. Students will also explore popular methods and principles in data analysis and data visualization.

COURSE CODE: qm877

In this bootcamp, students will learn the most essential aspects of Python programming. The topics are tailored toward data analysis; no prior programming experience is required. The course will cover variables, data types and data structures, DataFrames, conditionals, loops, and functions. We will also cover reading and writing raw files and the core APIs in analysis and visualization. With the basics under our belt, we will complement it with some of the most popular libraries for data analysis in Python, such as Pandas and Numpy for data manipulation, Matplotlib and Seaborn for visualization, and Jupyter Notebook for reporting. These packages will facilitate workflow and enhance the basic Python functionalities. Using them, one can effortlessly clean up a dataset, create elaborate plots, analyze and summarize the data, and produce presentable reports. During this module, students will solidify their new skills by applying the concepts they have learned to analyze several datasets. Students will have a chance to live-code during the sessions and troubleshoot their code with their classmates and the instructor. Students will walk out of this bootcamp with newly-forged Python coding skills, knowledge of several of the most important data science libraries and tools, and the resources for learning more.

COURSE CODE: qm880

The modeling process illustrated throughout the course will significantly improve students’ abilities to structure complex problems and derive insights about the value of alternatives. You will develop the skills to formulate and analyze a wide range of models that can aid in managerial decision-making in the functional areas of business. These areas include finance (capital budgeting, cash planning, portfolio optimization, valuing options, hedging investments), marketing (pricing, sales force allocation, planning advertising budgets) and operations (production planning, workforce scheduling, facility location, project management). The course will be taught almost entirely by example, using problems from the main functional areas of business. This course is not for people who want a general introduction to or review of Excel. This course is for students who are already comfortable using Excel and would like to use it to create optimization and simulation models.

COURSE CODE: fe870

This course introduces the analysis and management of risk in the context of financial institutions. The objective of the course is to provide a conceptual framework for thinking about financial risk, covering both theoretical background and practical implementation

COURSE CODE: hm817

For students interested in enhancing their skills for positions in the rapidly growing field of healthcare information technology, this course utilizes healthcare delivery, life science, and business leaders to deliver current perspectives and trends in the use of information technology (IT) to enhance patient care outcomes while delivering more cost-effective care. Students explore various methods and approaches that can be applied to both develop and evaluate IT systems encompassing electronic medical records, administrative systems, healthcare mobile applications, and the emerging field of digital therapeutics. The course provides strategic perspectives important to the healthcare chief information officer, chief medical information officer, other managers, prospective healthcare IT entrepreneurs, and users of both clinical and administrative IT systems. Its focus is not on the technical specialist.

COURSE CODE: is811

COURSE CODE: is838

COURSE CODE: is841

The widespread proliferation of IT-influenced economic activity leaves behind a rich trail of micro-level data about consumer, supplier and competitor preferences. This has led to the emergence of a new form of competition based on the extensive use of analytics, experimentation, and fact-based decision making. In virtually every industry the competitive strategies organizations are employing today rely extensively on data analysis to predict the consequences of alternative courses of action, and to guide executive decision making. This course provides a hands-on introduction to the concepts, methods and processes of business analytics. We will learn how to obtain and draw business inferences from data by asking the right questions and using the appropriate tools. Topics to be covered include data preparation, data visualization, data mining, text mining, recommender systems as well as the overall process of using analytics to solve business problems, its organizational implications and pitfalls. Students will work with real world business data and analytics software. Where possible cases will used to motivate the topic being covered. Prior courses in data management and statistics will be helpful but not required.

COURSE CODE: is843

This Level 3 analytics course will cover how to perform statistical analysis of large datasets that do not fit on a single computer. We will design a Hadoop cluster on Google Cloud Platform to analyze these datasets. Utilizing Spark, Hive, and other technologies, students will write scripts to process the data, generate reports and dashboards, and incorporate common business applications. Students will learn how to use these tools through Jupyter Notebooks and experience the power of combining live code, equations, visualizations, and narrative text. Employer interest in these skills is very high. Basic programming in python (e.g. IS717/IS756), and basic analytics (e.g. IS833/IS834) are prerequisite.

COURSE CODE: mk842

This course introduces students to machine learning techniques that can be used to analyze business data. Through a series of lectures and projects, students will learn about modern machine learning algorithms, how to use these algorithms in the R programming language, derive actionable insights from data, and effectively communicate their findings to a business audience. The goal of the course is to bridge the gap between managers and data-scientists by creating an understanding of modern analytics methods, and the types of business problems to which they can be applied. No prior programming skill are required. The course was previously offered under the title “Digital Marketing Analytics,” but does not overlap with MK876; students may take both courses for credit.

COURSE CODE: mk852

This course will focus on developing marketing strategies driven by marketing analytics. Topics covered include market segmentation, targeting, and positioning, new product test marketing, market response models, customer profitability, social media, and marketing resource allocation. The course will draw on and extend students’ understanding of issues related to quantitative analysis and principles of marketing. The course will use a combination of cases, lectures, simulations, and a hands-on project to develop these skills.

COURSE CODE: mk864

This course focuses on the practical needs of the marketing manager making pricing decisions. Students learn the techniques of strategic analysis necessary to price more profitably by evaluating the price sensitivity of buyers, determining relevant costs, anticipating and influencing competitors' pricing and formulating an appropriate pricing strategy.

COURSE CODE: mk876

COURSE CODE: mk878

COURSE CODE: mo860

This course focuses on developments in People Analytics, an evolving data-driven approach to employee decisions and practices. The course covers theory, practice, and methods that are critical for addressing people-related challenges at companies, such as hiring, retaining, evaluating, rewarding performance, and managing teams and social networks, to name a few. By drawing on the latest company practices, research, and cases studies, this course will help students apply people analytics to achieve organizational objectives and to advance in their own career. While a good background in basic statistics and/or analytics is helpful, it is not required for success in the course. Students will gain experience using analytics in a safe learning environment. We will also focus on how to apply insights to align people strategies with the organization’s broader goals.

COURSE CODE: om840

Lean and Six Sigma are powerful improvement methodologies that promote process improvement, cost reduction and significant enhancement of bottom-line profitability. The purpose of this course is to thoroughly examine the concept of quality, to define it in terms that are useful for managers, to survey the ideas of major quality thinkers and theorists, to develop proficiency in the use of quality tools, and to consider the challenges of quality program implementation in real business situations. Throughout the course we will investigate similarities and differences between quality management in manufacturing and service contexts. The course has three major objectives. The first goal is to define quality and explore important philosophies and useful frameworks for managers or consultants. The second goal is to focus on the Lean and Six Sigma tools available for the pursuit of lasting quality improvements. The third is to bring the experiences of Lean Six Sigma practice into the classroom. We’ll benefit from the expertise and experience of Lean and Six Sigma professionals who will help us to understand the challenges of Lean and Six Sigma implementations and analyze the lessons they have learned from projects they have undertaken.

COURSE CODE: om851

This course examines supply chain practices that reduce environmental impact for a firm These include eco-efficiency initiatives such as reduction in waste, energy and water usage, green logistics, product design for recycling, and supplier management. It covers additional topics such as complexity of supply chains, environmental impact assessment, the circular economy, food waste, eco-labeling, and sustainable business models (e.g., through servicing).

COURSE CODE: om854

This course presents tools and modeling frameworks that are relevant to solving today's supply-chain problems. The class will offer a mixture of case discussions, lectures, games, and outside speakers. Case discussions will cover subjects including designing new-product supply chains, optimizing inventory levels, quick response, the role of B2B exchanges, and managing capacity for short life-cycle products. Games, including the distribution game, the OPT game, and the Beer Game, will reinforce the concepts in a constructive way. Finally, outside speakers will present real-world examples of how supply-chain models are being deployed in practice. This course is for students who will be working in consulting or supply-chain management. For those interested in finance or marketing, the course provides solid exposure to an area that is integral to product-focused companies.

COURSE CODE: om855

Projects are increasingly the way that work gets done in companies of all types and sizes. In this new course you will learn the strategic dimensions of project management, including critical aspects of project selection, definition, planning, execution, and monitoring. Concepts and approaches for dealing with complexity, uncertainty, vague mandates, temporary staff, partners, stakeholders, dynamic risk, and time-critical deadlines are emphasized. Cases and readings cover a wide range of industry and organizational contexts. This course requires that students apply these topics and considerations to a real project of their choice either by analysis of publicly available information or direct field study. Many MBAs are tested on the job through tough assignments in project settings. Your performance there is highly visible. Doing especially well can accelerate your subsequent career opportunities. Prepare now for success in strategic project management by developing the skills and perspectives covered in OM855!

COURSE CODE: pl855

This course is designed as a multi-dimensional approach to understanding the energy sector. This includes production, development, distribution, financing, and consumption relating to the two distinct sectors – Power Generation and Transportation, both domestically and internationally. For Power Generation, we will explore the fundamentals of Generation, Transmission (G&T), and Distribution as well as major feedstocks, including wind, solar, nuclear, natural gas, and coal. This includes an in-depth discussion of both challenges and opportunities inherent to altering the current system.