This course is Layer 1 — “Self” — of the AI leadership journey: the leader’s personal competency with AI. Generative AI produces confident, specific answers in seconds. The hard part is no longer getting an answer — it is telling an insight from a hallucination, and owning what happens next.

That judgment cannot be delegated. Across five hands-on sessions, students direct AI agents (Claude Code) to build real, working business artifacts — a board deck, a private knowledge base, a BI dashboard, a DCF valuation, and a packaged AI agent — and learn the managerial judgment calls the AI cannot make. Every session pairs a real business task with hands-on practice and a debate in which students take a position.

In the rapidly evolving digital landscape, Generative AI has emerged as a transformative force for businesses across industries. This course, "Generative AI for Business," is designed to equip professionals with the knowledge and skills to leverage Generative AI technologies to solve complex business problems, enhance creativity, and drive innovation. By focusing on practical applications of Generative AI, including prompt engineering, semantic search, image generation, and Retrieval-Augmented Generation (RAG), Agentic AI, participants will learn how to effectively implement these tools to gain a competitive edge.

This course is ideal for business professionals, entrepreneurs, marketing specialists, product managers, and anyone interested in harnessing the power of Generative AI to solve business challenges. Whether you are looking to improve customer experiences, streamline operations, or foster innovation within your organization, this course will provide you with the tools and insights needed to succeed.

The course will provide students with a remarkably useful and essential set of business math concepts and methods for understanding and analyzing individuals’ and firms’ economic decisions. We will study several key concepts in the microeconomic foundation of managerial decision-making. Topics covered include (i) demand, supply, and market equilibrium; (ii) optimal pricing strategies under competition; (iii) utility function and risk attitude; (iv) information asymmetry and problems of adverse selection and moral hazard; and (v) game theory and strategic decision-making. As such, this course serves as a “tools” course for making analytical business decisions. The course will be presented through lectures, exercises, and student-led discussions.

Harvard Business Review called “Data Scientist: The Sexiest Job of the 21st Century”. In the past decade, the growing accessibility of large-scale data has paved the way for the field of data science to become in-demand professions. The course will introduce a number of useful data science-related libraries in the Python ecosystem such as pandas, numpy, matplotlib, and seaborn. Students will further advance their programming and analytical skills in Python using Pandas and numpy libraries. Through case studies and hands-on exercises, students will gain a deep understanding of how to solve data analytics problems in real-world situations.

Machine learning (ML) has given rise to countless artificial intelligence (AI) applications across industries. This course builds a broad conceptual foundation across the major paradigms of modern AI — supervised and unsupervised machine learning, generative AI, and agentic AI. The goal is to enable students to understand the conceptual basis for many AI products and services, for them to engage confidently with the AI concepts and terminology they encounter in business. We approach these topics from a production perspective, covering various stages in the AI development life cycle. We illustrate real application problems with business examples spanning a range of data types. We also discuss the impact of AI on productivity, and the value AI can create for organizations. Throughout the course we emphasize ethical issues, enterprise risk, and governance issues surrounding AI development and deployment.

Competitive Strategy in the Age of AI is about creating persistent superior performance for organizations in general and business firms in particular when firms face digital challenges. The thematic focus of this course is competitive advantage and the pervasive concept is that of strategy in a digital era. This course is concerned with both the determination of the strategic direction and the management of the strategic process. Our perspective in this course will be that of a general manager whose responsibility is the long-term health of an entire organization or a major division of an organization. This perspective enables us to view the organization in an overall fashion in the context of its environment. It requires that the students integrate the concepts, knowledge, and skills acquired in previous functional courses and creatively apply them to the understanding and analysis of competitive strategy issues. The course is organized around the following themes in competitive strategy: the concept of strategy, role of strategists, and the strategic decision making process; external analysis: industry structure and competitor analysis; internal analysis: firms’ resources and capabilities; business strategy: cost leadership strategy and industry positioning; business strategy: differentiation strategy; core competence; integrating external and internal analyses; changes in structures and strategies; identifying constraints on changes and transformation processes.

The major objectives of this course for students include the development of 1) a general management perspective: thinking strategically with a focus on digital components; 2) working knowledge of fundamental strategy concepts and issues; and 3) basic skills of analyzing strategic issues facing your current/future organization and your professional career.

We will survey historical perspectives, contemporary theories, and practical applications to help students develop a broad understanding of the various strategy issues. This course aims to expose the students to rigorous theoretical analysis, yet, at the same time, strives for practical relevance to real world business practice.

The pedagogical approach used in this course is a combination of lecturing, class discussion, case analysis, and group study. The case method has been one of the most effective means of management education, allowing students to tackle real business problems.

The purpose of this short module is to familiarize you with the strategic marketing decisions companies need to make while building a truly global brand. This module asks you to reflect on how modern firms create a value proposition for their customers, and how they capture the value they have created. Starting with the unique positioning of a firm’s product or service, we will discuss how firms integrate the 4Ps marketing mix elements (product, promotion, place, and price) into a coherent marketing strategy. We will examine why some brands are merely good while others are great, how to align positioning strategy with your tactical decisions, how firms can achieve competitive advantage by creating unique value for their customers, and how firms can achieve profitability by creatively capturing the value they have created.

The course aims to provide students with a comprehensive understanding of global business environment. It introduces the most fundamental concepts in macroeconomics and international economics that underpin the global economy. The course will help students understand the role of international trade and finance as well as emerging trends and currents that shape the global business landscape and help evaluate policy choices with relevant analytical tools. In specific, students will be presented with materials that constitute the core of economists’ viewpoints in today’s global economy: (i) what determines economic growth and causes fluctuations in outputs; (ii) the role of central banks and monetary policy in global economy; (iii) forces that drive financial markets and financial crises, and their impact on the world economy; and (iv) factors that influence international trades and the sources of conflicts. The course will discuss roles played by the governments, central banks, and financial institutions, and examine investment and strategic issues faced by businesses in the global economy. The course will be presented through lectures, exercises and student-led discussions of cases and readings.

Business managers must understand accounting information because it is an integral part of planning, reporting and control functions. This course is designed to familiarize the students with the basic elements of financial planning, reporting and control functions based on the financial accounting information. This course is to help the students learn (1) how to comprehend and interpret financial statements and (2) how to build earnings forecast models. The course is designed for anyone who is interested in pursuing a career in corporate finance and investments as well as strategy and management.

The learning objective of the course is to help students become conversant in concepts and techniques used in a firm’s investment appraisal and financing decisions. The course will review traditional methods such as NPV and IRR, and examine several issues in project valuations in practice, such as sensitivity and scenario analysis, forecasting cash flows, estimating the cost of capital, and measuring the impact of leverage, taxes, inflation, foreign exchange, and other complexities. The course will also study firms’ financing decisions, i.e., capital structure, and examine the trade-offs between debt and equity financing. Students will work with cases, and routinely implement spreadsheet models of cash flows as a part of case assignments. The course is suitable for anyone who is interested in evaluating firms’ investment decision-making, either from managers’ or market analysts’ perspectives.

Business forecasting is an essential function for any organization seeking to make data-driven decisions. Using machine learning and traditional statistical modelling, businesses can gain insights into future market trends, customer behavior, and optimal resource allocation. This course provides an in-depth overview of classic and modern forecasting techniques with a focus on practical applications. Students will learn to think deeply about conceptual issues in modelling, and be required to implement forecasting and evaluation techniques using statistical software.

This course is designed to learn the fundamental concept of AI&ML methods and how to apply AI and ChatGPT to real business problems through hands-on projects. Rather than focusing heavily on mathematical theory, the course emphasizes:

• using ChatGPT as a daily analytical partner
• learning the core concepts of machine learning and LLMs
• building practical AI tools and prototypes
• translating AI results into business decisions and executive communication

The instructor introduces the core concepts briefly, while most class time is spent on project-based practice using ChatGPT + Python + Colab.

Accounting is the “language of business” and thus essential for virtually any business and personal transactions. This is why “accounting” is a core course in business school programs. When making management decisions (i.e., planning and implementing business strategies, and evaluating performances, etc.), managers use various kinds of financial (and non-financial) information. In this course, our focus is on how they do (and should do) that in a variety of decision-making contexts. We will also study how managers use accounting information to motivate and evaluate management performance, i.e., for the purpose of control. At the end of the course, we will briefly explain financial statements, produced by firms for external reporting (i.e., financial accounting).

Although based on economic common sense, it is easy to misuse accounting information for managerial decisions, which could have disastrous consequences for you and your company, as we’ll see. Making right decisions will boost your productivity and effectiveness, and give you an advantage over your competitors. Main topics to be covered include cost concepts, cost-volume profit (CVP) analysis, decision making using relevant cost and revenue (including opportunity costs), cost allocation, decentralization and responsibility accounting, and performance evaluation.

Simply speaking, accounting is much like playing golf or tennis. While it may be enjoyable to watch someone else play the game, there is no way to learn how to play the game unless you do it yourself and actively participate in the entire learning process. This means that you need to do readings before and after class, participate in class discussion, and work on problems and cases to strengthen your understanding. Remember that you have invested a huge amount of financial and non-financial resources in this program. A small amount of your incremental investment will give you a large return.

This course is designed to train students to become more knowledgeable and effective data scientists by mastering Deep Learning techniques for real-world business applications. By learning hands-on implementation of high-level Deep Learning software such as TensorFlow and Keras, students will develop practical skills in building and optimizing deep learning models. This course emphasizes intuition and application over rigorous mathematics, so students are expected to have a basic understanding of Python, Linear Algebra, Calculus, and Probability. Students will explore fundamental models such as Perceptrons, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs). After learning these models, students will apply them to business challenges such as product image classification and fraud detection. By the end of this course, students will have a strong understanding of the deep learning toolbox, which will enable them to analyze complex business data and effectively apply these concepts in their professional careers.

This course aims to equip participants with a solid understanding of the major concepts and frameworks for assessing and formulating marketing strategies. We will focus on the essence of marketing activities, which is about creating, communicating, delivering, and exchanging offerings that have value for customers. This course will introduce structured and quantitative approaches to identifying, understanding, and solving problems marketers would encounter. In particular, we will help you develop analytical skills and learn to make sound decisions regarding how to focus resource on specific consumer segments, how to develop an effective mix of marketing communication effort, how to choose the right channel to deliver the products or service, and how to set price to capture value for the firm.

As corporate data is growing exponentially, understanding the foundations of how to manage and work with large databases is an essential starting point of business analytics. This course will provide you with a solid understanding of how to use and design databases in real-world situations. You will learn the fundamentals of Database Management Systems (DBMS) and the SQL language for data analysis. Using a robust SQL database system allows you to work with big data and access information quickly and efficiently. SQL is also an excellent adjunct to programming languages used in data science, such as R and Python. The course will also cover a brief introduction to the No-SQL database for working with large sets of distributed data.

This course is for beginners who want to perform data analysis with SQL and build database design skills. More specifically, students will develop the necessary skills in building powerful databases and writing for data cleaning, transformation, and storytelling. The classes will be lecture-based, with lots of hands-on exercises using real data sets you will likely encounter in the real world.

The Applied Business Projects course provides students with an opportunity to apply the knowledge and skills developed throughout the AI MBA program to real-world business challenges. Students will work on practical projects that address problems such as business process improvement, customer experience, data-driven decision-making, and AI-enabled innovation. Through project-based learning, students will define business problems, analyze data and organizational contexts, develop and evaluate potential solutions, and translate their findings into actionable recommendations. Emphasis is placed on bridging business strategy, analytics, and AI to create practical and measurable business value. By completing an applied project, students will strengthen their problem-solving, collaboration, and communication skills while gaining hands-on experience in driving business innovation through data and AI.

The Business Analytics Workshop will equip students with practical, hands-on skills at the intersection of business analytics, software development tools, and emerging AI technologies. Building on prior exposure to programming and modeling fundamentals, this workshop focuses on real-world applications through cutting-edge tools like VS Code, Git, GitHub Copilot, and no-code/low-code AI agent platforms. Participants will engage with case-based exercises and live demonstrations to explore how modern data-driven teams collaborate, code, and build AI-enhanced solutions in agile business environments. This workshop seeks to bridge analytical modeling, modern software practices, and AI development workflows.

The Applied Business Projects course provides students with an opportunity to apply the knowledge and skills developed throughout the AI MBA program to real-world business challenges. Students will work on practical projects that address problems such as business process improvement, customer experience, data-driven decision-making, and AI-enabled innovation. Through project-based learning, students will define business problems, analyze data and organizational contexts, develop and evaluate potential solutions, and translate their findings into actionable recommendations. Emphasis is placed on bridging business strategy, analytics, and AI to create practical and measurable business value. By completing an applied project, students will strengthen their problem-solving, collaboration, and communication skills while gaining hands-on experience in driving business innovation through data and AI.