What you'll learn

  • Capabilities in technical, analytical, and operational areas to advance your firm’s position in the global market.

  • Core data analysis and management skills.


  • How to keep up with a business world that is constantly impacted by machine learning and artificial intelligence.

  • An in-depth understanding of modern technologies and practices in next-generation analytics, such as blockchain, digital strategy, and AI/ML.

  • How to interpret your findings and use them to uncover valuable business insights.

  • How to apply these concepts to your organization, with a mind toward maximizing efficiencies and outcomes.

Course description

Unlike many other offerings, the Harvard Business Analytics Program features a blended format with live online and in-person components.

The Harvard Business Analytics Program consists of six core courses, two seminars, and two in-person immersions. The rigorous curriculum delivers an authentic Harvard experience and consists of entirely new courses that are frequently updated to adapt to industry changes and emerging technologies. The program can be completed in as little as nine months.

Participants who are accepted into the upcoming cohort can apply for an income-based scholarship of up to 30%. To secure the scholarship offer, participants who haven't already made an enrollment deposit must do so immediately, as scholarships are awarded on a first-come, first-served basis to a limited number of applicants.

Course Outline

Competing in the Age of AI

Artificial intelligence (AI) is revolutionizing the way today's businesses compete and operate. By putting AI and data at the center of their capabilities, companies are redefining how they create, capture, and share value—and are achieving impressive growth as a result. This course will delve into new AI-based business models and operational approaches. Through global case studies on market leaders and innovative startups in diverse industries, the course will explore a range of capabilities that can help your business succeed in today's data-driven environments. Along with learning how to unlock new growth potential, you will deepen your understanding of ethical challenges that come with leveraging massive amounts of data and sophisticated analytics. You will further examine the ethics of AI through real-world case studies that have widespread debate about issues such as academic freedom, corporate responsibility, and bias in AI systems. Recent developments in generative AI are discussed including how large language models are developed and how they can be used by individuals and businesses. Course faculty demonstrate conversing and performing data analytics with ChatGPT.

Programming and Data Systems

Combining technical guidance, analysis of real-world cases, and hands-on coding assignments each week, this initiative enables individuals to navigate technological choices effectively, even without a technical background. Covering areas such as artificial intelligence, cloud computing, networking, privacy, scalability, and security, the program places a special focus on web and mobile technologies. Participants will learn the basics of coding with SQL and Python, and be introduced to fundamental concepts in decision trees, neural networks, LLMs, other types of AI models, and generative AI in order to understand what AI can do for their organization. 

Leadership, Innovation, and Change

This course places a strong emphasis on the leader’s role in enhancing the execution of their existing strategy to outperform competitors, alongside their involvement in driving strategic innovation. We employ the congruence model that links strategy to execution through alignment of culture, people, tasks, structure, and executive leadership. Because ambidexterity requires leaders that can deal with punctuated change and paradoxical strategies, our program concludes with what we know about ambidextrous leadership and leading large system change.

Operations and Supply Chain Management

This program will focus on overseeing product availability, particularly within the dynamic landscape of swift product expansion, brief product life cycles, and interconnected networks of suppliers and customers on a global scale. The key topics examined include inventory management, distribution economics, demand forecasting, supplier management, and the potential benefits of using AI and machine learning to work with data. 

Foundations of Quantitative Analysis

This program serves as an initiation into employing statistical methodologies for tackling business challenges. Key elements of the curriculum include methods for describing and summarizing data, the fundamentals of probability, the basics of study design and data collection, and statistical inference. Data analyses, simulation, and design issues are implemented in the statistical computing package R run within the RStudio interface.

Leadership and People Analytics

Participants will develop practical skills to analyze data in a manner that compliments the frameworks and intuitions typically employed to steer their managerial decisions on people issues. Anchored in data, this program will equip participants with an analytic approach for assessing the diverse factors impacting individual, team, and organizational performance, ultimately resulting in more impactful interventions and initiatives.

Data-Driven Marketing

The once qualitative and instinct-driven aspect of business functions (think “Mad Men”) has evolved into a data-driven profession that relies on quantitative insights on how best to optimize ad creation and placement and influence consumer purchase behavior. This course focuses on the benefits that AI and machine learning bring to marketing including enhanced personalization and customization, as well as pricing optimization and automation. Participants will also learn how AI affects change management and algorithmic bias. This course will examine the ways in which marketing has changed and the new skills and capabilities needed to succeed in this function. 

Data Science Pipeline and Critical Thinking

This program will take a holistic approach to helping participants understand the key factors involved in the data science pipeline, from data collection to analysis to prediction and insight. The curriculum will expand on the application of AI in data science by looking at the role of machine learning. Topics such as large language models, supervised learning, unsupervised learning, Bayes’ Theorem, and deep learning will be explored throughout the program. Projects will give participants hands-on experience developing and running a data science pipeline to ensure that the correct business predictions are being made.


In addition to the online learning components of the program, you will have the opportunity to attend two 2.5-day, on-site and in-person immersions held at the Harvard Business School campus in Boston.

During these experiences, you'll get to engage in direct interactions with your classmates, establish connections with faculty members, and connect with influential figures in the industry during evening events. You’ll also have the chance to tour the Harvard campus and participate in hands-on guided learning exercises. Throughout your experience, you’ll gain an in-depth understanding of deep learning and neural networks, and use the HBS case method to formulate solutions to real-world business scenarios as a way to understand relevant challenges in the industry. Recent topics include fairness in algorithms, data privacy, leading transformational change, and the evolving landscape of AI.


Dorothy and Michael Hintze Professor of Business Administration
Edward W. Carter Professor of Business Administration and Chair of the General Management Program, Harvard Business School
Thomas D. Casserly, Jr. Professor of Business Administration, Harvard Business School
Senior Preceptor in Statistics, Harvard University
Herchel Smith Professor of Computer Science, Harvard University

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