Hoos’ List

This course is an introduction to consumer, product, and market analytics. You will learn key concepts in brand positioning, customer segmentation, and consumer behavior. The course will expose students to basic market research methods and measurement considerations in designing and conducting market research. The course will also cover basic statistics techniques using SPSS and R-Studio.

Business Analytics is useful to the extent that it impacts decision making in an enterprise. Critical to having impact is a thorough understanding of its strategy. This course develops frameworks and tools to analyze the strategy of an organization and develops the skills to evaluate decisions inside an organization. This course will connect your analytical skills with the ability to influence the enterprise as it executes its strategy.

In this course, we will explore approaches for structuring, quantifying, and analyzing common business decisions. We will also explore the various uses of data and statistical inference to drive better decision making. This course aims, in part, to improve your analytical skills by gaining insight into risk and uncertainty. Tools and techniques to support this objective will include decision trees, simulation, hypothesis testing, and regression.

You will be introduced to leading analytical techniques in marketing and how marketers use marketing data to design cutting-edge marketing strategies. We will use data analysis to support marketing decisions and explore techniques for product line pricing, demand forecasting, customer segmentation, and customer lifetime valuation. We will use a hands-on approach, and the topics covered in this course are relevant to current marketing practice.

In this course, students will gain exposure to and practice with the concepts and tools used to leverage data at scale and create value. The concepts and tools covered include data visualization, machine learning, and cloud computing. Through materials designed for the novice, students will be introduced to coding in Python and learn to develop predictive models from large datasets. Students will also learn data visualization in Tableau.

Data visualizations weave information into insights that add business-relevant value. Visual storytelling creates compelling arguments that inspire people to act. Analyzing data sets, finding insights, and turning insights into persuasive storytelling are critical to persuading audiences. We will explore constructing data visualizations using storytelling, visuals, key language, callouts, BLUFs, and other related data visualization elements.

You will be introduced to the strategy consulting process, identify, and refine the skills for successful consulting engagements for a wide variety of analytics projects. The first half of the course will focus on the cognitive processes involved in framing and designing the engagement. The other half will address a more tactical set of issues around engagement work planning, data gathering, field interviewing, and communicating with clients.

This course introduces advanced analytical multivariate techniques used in marketing to understand customer and employee attitudes and behavior from data to gain market intelligence plus target and segment customers and employees that maximizes important marketing metrics. Topics include advanced regression techniques, logistic regression, path analysis, cluster and discriminant analysis, and experimental design. You will use SPSS and R.

You will learn some of the world's most powerful predictive models. We cover a variety of machine learning algorithms and survival models. We have a hands-on approach, working on real case studies to deepen our understanding of how machine learning solves business problems. You will be exposed to Python and learn to write Python code. In teams, you will compete with peers to develop the best predictive models using machine learning algorithms.

Covers end-to-end processes relating to the capture, organization, use, and protection of data for analytical purposes. You will learn how to build an optimized relational database and use SQL to extract data to support an organization's analytics strategy and provide important managerial insights from raw data. Extraction, transformation, load (ETL) and data privacy/security will also be discussed in the context of modern organizations.

Prototyping and Product Development is an action-oriented and project-based course. You and your team will identify a problem, develop multiple prototypes that address the problem, and test prototypes through iterative experimentation. Class sessions will be a mix of hands-on exercises, selected readings, and guest speakers. The majority of class time will be devoted to project work to help teams complete their prototypes.

We cover natural language processing, deep learning, and artificial intelligence to apply them to text and image data. You will learn algorithms that are the backbone of technologies used by Google and Tesla. You will also learn about Transformers, a revolutionizing concept that has caused a paradigm shift in artificial intelligence. In teams, you will compete with peers to develop the best predictive models to process and analyze text data.

Agile has become the de facto approach to innovation initiatives. For the analyst, the practice of agile provides an opportunity to instrument these initiatives with analytics such that the analytics consistently and purposefully help drive better decisions and customer experiences. In this course, students will apply agile to leading with evidence-based, analytics-driven decisions.

Teams will solve an analytics challenge from a sponsoring company. The company will provide the data and the problem. You and your team will design a solution in the form of a set of visualizations and a model and assess the business impact in conjunction with the sponsoring company. Key questions: How much money will the proposed solution save? How many new customers will the proposed solution attract? The core deliverable is a presentation.

In the second capstone course you will assess the business impact of your solution and should be done in conjunction with the sponsoring company. Key assessment questions may include: a) how much money (or other resources) will the proposed solution save? b) How many new customers will the proposed solution attract? c) how much money will current customers spend? The core deliverable is a report on the business impact your proposed solution.

In this course, you will build a more accurate and up-to-date understanding of what drives human behavior, understand the nature and complexity of moral issues that digital technology and analytics raise, and practice making decisions that balance your ability to use analytics and benefit people.

This course exposes students to how business analytics are used in various global managerial contexts. Students develop a toolkit of analytical competencies while gaining experience in solving business problems and communicating analytical findings.

This course is an introduction to consumer, product, and market analytics. You will learn key concepts in brand positioning, customer segmentation, and consumer behavior. The course will expose students to basic market research methods and measurement considerations in designing and conducting market research. The course will also cover basic statistics techniques using SPSS and R-Studio.

Business Analytics is useful to the extent that it impacts decision making in an enterprise. Critical to having impact is a thorough understanding of its strategy. This course develops frameworks and tools to analyze the strategy of an organization and develops the skills to evaluate decisions inside an organization. This course will connect your analytical skills with the ability to influence the enterprise as it executes its strategy.

In this course, we will (a) explore approaches for structuring and analyzing common business and financial decisions and (b) discuss respective analytical methods. We will explore what factors drive a firm's value and how a manager should exploit information at hand to to improve his/her strategic decisions. This course aims, in part, to improve your analytical skills by gaining insight into risk and uncertainty.

In this course, we will explore approaches for structuring, quantifying, and analyzing common business decisions. We will also explore the various uses of data and statistical inference to drive better decision making. This course aims, in part, to improve your analytical skills by gaining insight into risk and uncertainty. Tools and techniques to support this objective will include decision trees, simulation, hypothesis testing, and regression.

You will be introduced to leading analytical techniques in marketing and how marketers use marketing data to design cutting-edge marketing strategies. We will use data analysis to support marketing decisions and explore techniques for product line pricing, demand forecasting, customer segmentation, and customer lifetime valuation. We will use a hands-on approach, and the topics covered in this course are relevant to current marketing practice.

In this course, students will gain exposure to and practice with the concepts and tools used to leverage data at scale and create value. The concepts and tools covered include data visualization, machine learning, and cloud computing. Through materials designed for the novice, students will be introduced to coding in Python and learn to develop predictive models from large datasets. Students will also learn data visualization in Tableau.

Data visualizations weave information into insights that add business-relevant value. Visual storytelling creates compelling arguments that inspire people to act. Analyzing data sets, finding insights, and turning insights into persuasive storytelling are critical to persuading audiences. We will explore constructing data visualizations using storytelling, visuals, key language, callouts, BLUFs, and other related data visualization elements.

You will be introduced to the strategy consulting process, identify, and refine the skills for successful consulting engagements for a wide variety of analytics projects. The first half of the course will focus on the cognitive processes involved in framing and designing the engagement. The other half will address a more tactical set of issues around engagement work planning, data gathering, field interviewing, and communicating with clients.

This course introduces advanced analytical multivariate techniques used in marketing to understand customer and employee attitudes and behavior from data to gain market intelligence plus target and segment customers and employees that maximizes important marketing metrics. Topics include advanced regression techniques, logistic regression, path analysis, cluster and discriminant analysis, and experimental design. You will use SPSS and R.

You will learn some of the world's most powerful predictive models. We cover a variety of machine learning algorithms and survival models. We have a hands-on approach, working on real case studies to deepen our understanding of how machine learning solves business problems. You will be exposed to Python and learn to write Python code. In teams, you will compete with peers to develop the best predictive models using machine learning algorithms.

Covers end-to-end processes relating to the capture, organization, use, and protection of data for analytical purposes. You will learn how to build an optimized relational database and use SQL to extract data to support an organization's analytics strategy and provide important managerial insights from raw data. Extraction, transformation, load (ETL) and data privacy/security will also be discussed in the context of modern organizations.

One of the core functions of leaders is making decisions. However, evidence repeatedly shows that leaders often make decisions that are systematically flawed despite the availability of data that might inform those decisions. This course exposes students to an array of decision-making biases and offers practical solutions for making better decisions, both as individuals as well as teams.

Prototyping and Product Development is an action-oriented and project-based course. You and your team will identify a problem, develop multiple prototypes that address the problem, and test prototypes through iterative experimentation. Class sessions will be a mix of hands-on exercises, selected readings, and guest speakers. The majority of class time will be devoted to project work to help teams complete their prototypes.

We cover natural language processing, deep learning, and artificial intelligence to apply them to text and image data. You will learn algorithms that are the backbone of technologies used by Google and Tesla. You will also learn about Transformers, a revolutionizing concept that has caused a paradigm shift in artificial intelligence. In teams, you will compete with peers to develop the best predictive models to process and analyze text data.

This course will introduce the latest practices and technologies for managing big data. It will first compare and contrast big data to relational data in both operational and analytical data systems. It will then explore modern technologies (e.g., Spark and NoSQL), cloud computing (e.g., AWS), and reference architectures for retrieving, storing, integrating and analyzing big data. Finally, it will demonstrate big-data-enabled AI applications.

Agile has become the de facto approach to innovation initiatives. For the analyst, the practice of agile provides an opportunity to instrument these initiatives with analytics such that the analytics consistently and purposefully help drive better decisions and customer experiences. In this course, students will apply agile to leading with evidence-based, analytics-driven decisions.

Teams will solve an analytics challenge from a sponsoring company. The company will provide the data and the problem. You and your team will design a solution in the form of a set of visualizations and a model and assess the business impact in conjunction with the sponsoring company. Key questions: How much money will the proposed solution save? How many new customers will the proposed solution attract? The core deliverable is a presentation.

In the second capstone course you will assess the business impact of your solution and should be done in conjunction with the sponsoring company. Key assessment questions may include: a) how much money (or other resources) will the proposed solution save? b) How many new customers will the proposed solution attract? c) how much money will current customers spend? The core deliverable is a report on the business impact your proposed solution.

This course is the third capstone project course. It asks each team to prepare and deliver an oral presentation to an audience that includes their classmates and the sponsoring company. Faculty will work with the teams to help them develop an effective approach to communicating their solution and its business impact. The main deliverables are the in-person presentation and a supporting deck of slides.

In this course, you acquire skills in analytics project scoping, planning, risk analysis and management, resource allocation and budgeting, monitoring, and real options thinking. You will use state-of-the-art software such as Microsoft Project and Jira to plan and execute large-scale projects. You will also consider the challenge of managing projects and develop an awareness of behavioral decision-making biases in project management.

In this course, you will build a more accurate and up-to-date understanding of what drives human behavior, understand the nature and complexity of moral issues that digital technology and analytics raise, and practice making decisions that balance your ability to use analytics and benefit people.

Creating the Future is a project-based course as an extension of the capstone projects completed during the program. You will be challenged to consider the organizational implications of the analysis you have completed in your capstone courses. You will learn to evaluate and understand organizational, strategic and ethical implications of the recommendations you have produced and broaden your perspective on how you approach business analytics.