Course Descriptions

Course information is subject to change. 

 

Mod 1

Enterprise Analytics I: Customers, Products and Markets

Description: This course is an introduction to consumer behavior, product development, and marketing analytics. You will learn to segment a market effectively, target groups for business-development, and how to price a product. This course will expose you to basic marketing research methods for evaluating communication and developing effective sales force as part of an enterprise-wide perspective of the marketing function and its value within an organization.

Credits: 1.5

Enterprise Analytics II: Organizations and Strategy

Description: High-performing organizations are driven by leaders who enable people and processes to be productive. This course helps students cultivate mind-sets and use tools to evaluate and influence the behavior of people inside an organization and be valuable members of a team. An integral part of any organization is how it coordinates tasks and collaboration – the process by which the firm delivers its product or service. Another key part of the firm is its strategy, or the way it chooses to compete in a market. This part of the course will develop students’ ability to analyze the organizational and external factors essential for crafting and executing a company’s strategy for sustained success. An important aspect of selecting a strategy will be the framing and analysis of decisions involving uncertainty, whether the uncertainty results from general conditions or the actions of competitors. In addition to a strategic perspective, this course will build skills for assessing and leading teams to execute strategy.

Credits: 1.5

Enterprise Analytics III: Financial Decision Making

Description: 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 improve his/her strategic decisions. This course aims, in part, to improve your analytical skills by gaining insight into risk and uncertainty.

Credits: 1.5

Mod 2

Customer Analytics I: Pricing

Description: This course examines the best ways to develop useful pricing analytics. Pricing is often one of the most analytically-driven decisions companies make. The course will focus not only on the development of appropriate analytics but also the application of these analytics across a diverse set of industries. This course was developed with and is co-taught by pricing experts from Boston Consulting Group’s Global Pricing Practice. As such, the course moves from material that requires mathematics and economics toward broader questions of how these quantitative tools can be used to inform overall strategy at the highest level of the organization.

Credits: 2

Data Analytics I

Description: 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.

Credits: 2

Leadership I: Management Communications

Description: You will receive guidance and hands-on experience to communicate effectively as managers and leaders. We will examine communication strategies essential for success in business and identify personal strengths and goals. You will improve your communication strategy and will help you appreciate the power of personal and organizational narratives but also deliver successful written documents, oral presentations, and data journalism.

Credits: 1

Leadership II: Strategy Consulting

Description: 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.

Credits: 1

Mod 3

Customer Analytics II

Description: 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.

Credits: 2

Data Analytics II

Description: The goal of the course is to introduce you to machine learning, some of the world’s most powerful predictive models. The course covers topics such as machine learning algorithms, overfitting, supervised learning, cross-validation, regularization, recursive partitioning, and assembling. You will be exposed to Python and learn to write Python code. In teams, you will enter forecasting competitions to develop predictions using these algorithms.

Credits: 1.5

Data Warehousing and Business Intelligence

Description: You will learn how companies store, retrieve, and mine data. The principles of data management, the process of ETL – extract, transform, and load, data security, integrity, and governance will be discussed. To mine data for basic business intelligence, you will manipulate data and create visualization that leaders use to manage and track business. You will learn to use SQL and Tableau to query databases and create visualizations, respectively.

Credits: 1.5

Leadership III: Digital Design

Description: The course focuses on the design of digital products and services. We will use design thinking to emphasize customer empathy, invention, optionality, and iteration. You will conduct qualitative and quantitative investigations on what product features will be valuable to a user. By the end of this course, you will able be to pair the design thinking and analytical skills to identify user needs and translate those into digital solutions.

Credits: 1

Mod 4

Customer Analytics III

Description: This course focuses on analytics in the digital marketing space through discussion of concepts, technologies, and tools necessary to support digital commerce. Emphasis is placed on tools and methodologies for bolstering web presence through web and search analytics. Specific topics include methods for analyzing and improving user experience, web traffic, online engagement, and conversion rates.

Credits: 1.5

Data Analytics III

Description: You will be introduced to natural language processing, deep learning and artificial intelligence including text analysis and image and voice recognition. You will work in Python to process a document’s key words, sentiments, and topics. As the main building block of deep learning and artificial intelligence, you will learn to run neural networks. You will use Google’s open-source TensorFlow to run neural networks for image recognition purpose.

Credits: 1.5

Managing Big Data

Description: In this course, you will be introduced to the concepts (i.e. data lakes and cloud computing), tools, and techniques for working with big data. You will learn to use software such as Hadoop and Spark. These tools enable large-scale data processing. The course contains readings, cases, and exercises. An example of an exercise is to build a recommender system that recommends a movie based on the new user’s and similar users’ preferences.

Credits: 1.5

Leadership IV: Software Applications

Description: Continuing the digital design theme in the Leadership courses, this course pushes you to tinker with software. As a leader in business analytics, you will likely build software applications to support analytics-driven decisions and work in interdisciplinary teams on product and system development. In this project, you will take a validated design and code it up. You will learn HTML, CSS, and Javascript plus analyze results in Google Analytics.

Credits: 1.5

Mod 5

Capstone Project: Solution Design

This course is the first of four capstone project courses. Each team will have an analytics challenge from a sponsoring company. The company will provide data and an analytics problem. You and your team will design a solution plus a working prototype of a model or a software application that executes some significant analytics function related to the challenge. Deliverables may include: the solution, model’s code, the piece of software, etc.

Credits: 1.5

Capstone Project II: Business Impact

Description: 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.

Credits: 1.5

Capstone III: Presentation/Management Communication

Description: 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.

Credits: 1.5

Leadership V: Agile Project Management

Description: This course teaches you to apply a disciplined yet adaptive approach to project management, which relies on iterative agile cadences. Building on Leadership III and IV courses, you will be able to: a) translate execution ideas into agile user stories, b) groom a story backlog based on project priorities, c) decompose a story backlog into actionable tasks, d) design a continuous delivery pipeline, and e) participate in a self-organizing team.

Credits: 1.5

Capstone Project IV: Presentation Feedback/Management Communication

Description: In this course you will learn strategies and best practices for evaluating analytics project presentations. Emphasis will be placed on how to examine both the content and delivery, including technical feasibility, problem-solution alignment, business value, storytelling ability, and communication quality. The course will encompass a combination of lectures, video recording feedback sessions, and peer group feedback presentations and discussion.

Credits: 0.5

Business Ethics and the Digital Age

Description: This course is designed to help you better recognize and incorporate ethical considerations into your decision-making, understand your own values, expose you to different values and beliefs, and provide a process for tackling difficult and morally ambiguous situations in business, ethics, and technology. We will use cases to surface moral responsibilities to stakeholders and equip you with key frameworks, terminology, and concepts.

Credits: 0.5

Creating Your Future

Description: 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.

Credits: 0.5