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Cross-Disciplinary Curriculum

Become Fluent in Data Analytics

Learn to Drive Your Business Forward

The Harvard Business Analytics Program curriculum is designed and delivered by leading faculty in artificial intelligence, business, data analytics, statistics, and more.

This one-of-a-kind certificate experience can only be found at Harvard—and can be completed in less than a year.

6

Core Courses

2

Online Seminars

2

On-Campus Immersions

9–18

Months to Complete

View program structure and course descriptions.

The Harvard Business School Case Method

The case method is hallmark to Harvard Business School and thoughtfully integrated into the HBAP curriculum. You and your classmates will examine 65+ case studies that showcase several kinds of real-world business challenges related to our subject matter.

The case method fosters intense debate as you and your peers collaborate to share your insights, challenge assumptions, entertain diverse viewpoints, and work together to arrive at a thoughtful conclusion.

This hands-on, collaborative technique immerses you in your learnings and better prepares you to strategically tackle problems in your own work, because when we put ourselves in an organization’s shoes, we learn a lot about business leadership in the 21st century.

“I’ve done quite a few AI/ML and Python certificates, but
none of them could replace the HBS case method.”

– Anferny Chen, HBAP ’18

Sample Program Structure and Courses

Learning to lead a digital transformation is a lot of work—but we know it’s not the only work you do. Our courses are rigorous but flexible for busy professionals, whether you pursue the certificate full or part time. Your schedule will include live, online classes complemented by self-directed, asynchronous coursework that you can complete on your own time. Learn more about the hybrid learning experience.

Standard Full Time

9

Months

3

Terms

11–25

Hours per Week

Standard Part Time

18

Months

6

Terms

10–14

Hours per Week

Standard 9-Month Program Structure

Term 1 (2 Courses, 8 Weeks)

expand_more

Digital Strategy and Innovation

The broad digitization of the global economy is resulting in enormous stores of varied data being generated and collected. Competitive advantage in the 21st century is accruing to companies that are able to make data-driven analytics and decision-making a core part of their growth strategy, their business development endeavors, and all aspects of their operations. Large companies like Google, General Electric, Alibaba, and Baidu have embraced data analytics as a core aspect of their product and operations strategy, and multitudes of startups are emerging to disrupt existing players through the clever leveraging of big data. Through global case studies on market leaders and innovative startups in diverse industries, the course examines the strategies and operational changes needed to make data analytics integral to your future success.

Taught by Marco Iansiti (HBS), Karim Lakhani (HBS), Antonio Moreno (HBS), and Feng Zhu (HBS)

Foundations of Quantitative Analysis

This course is an introduction to using statistical approaches to solve business problems. It introduces statistical concepts via a management perspective and places special emphasis on developing the skills and instincts needed to make sound decisions and become an effective manager. The main components of the course 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.

Taught by Mark Glickman (FAS), Mike Parzen (HBS), and Kevin Rader (FAS)

Seminar I (2 Weeks)

expand_more

Leadership, Innovation, and Change

An emphasis on data analytics and algorithms at the center of an enterprise also means that leaders will have to drive both innovation and large-scale organizational change. This course will focus on the leader’s role in both executing their current strategy better than their competitors as well as their role in shaping strategic innovation. We employ the congruence model that links strategy to execution through alignment of culture, people, tasks, structure, and executive leadership. We also explore the inertial characteristics of aligned organizations and the strategic importance of driving innovation streams. We explore building ambidextrous organizations, organizations that can both exploit their existing strategy as well as explore into new strategic domains. Because ambidexterity requires leaders that can deal with punctuated change and paradoxical strategies, our course concludes with what we know about ambidextrous leadership and leading large system change.

Taught by Michael Tushman (HBS) and Rory McDonald (HBS)

*You must complete Digital Strategy and Innovation before you take this course.

Term 1 Immersion (3 Days)

expand_more

In-Person Immersion at Harvard Business School Campus in Boston

During these in-person experiences, you will meet face to face with your classmates, network with faculty and industry leaders during nightly events, tour the Harvard campus, and participate in hands-on guided learning exercises. You will also use the HBS case method, formulating solutions to real-world business scenarios as a way to understand relevant challenges in the industry. Recent topics of discussion have included reputation systems, data sharing and security, and organizational leadership. Immersion dates are subject to change.

Term 2 (2 Courses, 8 Weeks)

expand_more

Operations and Supply Chain Management

Digital technologies and data analytics are radically changing the operating model of an organization and how it connects to its broader supply chain and ecosystem. This course emphasizes managing product availability, especially in a context of rapid product proliferation, short product life cycles, and global networks of suppliers and customers. Topics examined include inventory management, distribution economics, demand forecasting, and supplier management. The course emphasizes the “general manager’s perspective” in supply chains. Cases in the course illustrate that barriers to integrating supply chains often relate to behavioral issues (e.g., misaligned incentives or change management challenges) and operational execution problems that fall squarely in the domain of the general manager.

Taught by Ryan Buell (HBS), Dennis Campbell (HBS), Kris Ferreira (HBS), Jan Hammond (HBS), and V.G. Narayanan (HBS)

*You must complete Foundations of Quantitative Analysis before you take this course.

Programming and Data Science Systems

Modern business analytics requires executives and managers to be conversant with programming and data architecture. The aim of this course is to provide participants with the fundamental knowledge and practice needed to appreciate the challenges and opportunities related to developing robust and scalable systems that are at the core of business analytics by emphasizing mastery of high-level concepts and design decisions. Through a mix of technical instruction, discussion of case studies, and weekly programming projects, this course empowers participants to make technological decisions even if not technologists themselves. Topics include cloud computing, networking, privacy, scalability, security, and more, with a particular emphasis on web and mobile technologies. Participants emerge from this course with firsthand appreciation of how it all works and all the more confident in the factors that should guide their decision-making.

Taught by Henry Leitner (SEAS) and David Malan (SEAS)

Seminar II (2 Weeks)

expand_more

Leadership and People Analytics

People analytics is designed to help practitioners use data to improve people-related decisions. Participants will build hands-on skills to analyze data in ways that complement the frameworks and intuitions they would normally use to guide their managerial actions on people issues. At a deeper level, students in any job, organization, or industry context will sharpen their ability to think critically through the lens of rigorous analytics. Anchored in data, this course will equip participants with an analytic approach to diagnosing the varied forces that influence individual, team, and organizational performance, leading to more effective interventions and actions. While developing analytic skills and trying out tools and techniques, participants will come to appreciate the opportunities, limits, and tensions involved in using data analytics to inform people issues, while simultaneously gaining deeper insight into the substance of the business issues in question.

Taught by Jeff Polzer (HBS)

*You must complete Foundations of Quantitative Analysis, and Leadership, Innovation, and Change before you take this course.

Term 3 (2 Courses, 8 Weeks)

expand_more

Data-Driven Marketing

Marketing has been revolutionized and forever changed by data analytics. What used to be a qualitative and instinct-driven business function (think Mad Men) has now become 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 will examine the ways in which marketing has changed and the new skills and capabilities needed to succeed in this function.

Taught by Sunil Gupta (HBS), Ayelet Israeli (HBS), and David Parkes (FAS)

*You must complete Digital Strategy and Innovation, Programming and Data Science Systems, and Foundations of Quantitative Analysis before you take this course.

Data Science Pipeline and Critical Thinking
Ultimately, business analytics is about using data, analytics, and algorithms to make prescriptive predictions about future events and decisions. This course will take a holistic approach to helping participants understand the key factors involved, from data collection to analysis to prediction and insight. Projects will give students hands-on experience developing and running a data science pipeline to ensure that the correct business predictions are being made. Emphasis will be on merging technical skills with critical thinking to ensure that robust data science pipelines are being created for business benefit.

Taught by Joe Blitzen, Iavor Bojinov, Srikant M. Datar, and Hanspeter Pfister

*You must complete Digital Strategy and Innovation, Operations and Supply Chain Management, Programming and Data Science Systems, and Foundations of Quantitative Analysis before you take this course.

Term 3 Immersion (3 Days)

expand_more

In-Person Immersion at Harvard Business School Campus in Boston

During these in-person experiences, you will meet face to face with your classmates, network with faculty and industry leaders during nightly events, tour the Harvard campus, and participate in hands-on guided learning exercises. You will also use the HBS case method, formulating solutions to real-world business scenarios as a way to understand relevant challenges in the industry. Recent topics of discussion have included reputation systems, data sharing and security, and organizational leadership. Immersion dates are subject to change.

Standard 18-Month Program Structure

Term 1 (1 Course, 8 Weeks)

expand_more

Digital Strategy and Innovation

The broad digitization of the global economy is resulting in enormous stores of varied data being generated and collected. Competitive advantage in the 21st century is accruing to companies that are able to make data-driven analytics and decision-making a core part of their growth strategy, their business development endeavors, and all aspects of their operations. Large companies like Google, General Electric, Alibaba, and Baidu have embraced data analytics as a core aspect of their product and operations strategy, and multitudes of startups are emerging to disrupt existing players through the clever leveraging of big data. Through global case studies on market leaders and innovative startups in diverse industries, the course examines the strategies and operational changes needed to make data analytics integral to your future success.

Taught by Marco Iansiti (HBS), Karim Lakhani (HBS), Antonio Moreno (HBS), and Feng Zhu (HBS)

Term 2 (1 Course, 8 Weeks)

expand_more

Foundations of Quantitative Analysis

This course is an introduction to using statistical approaches to solve business problems. It introduces statistical concepts via a management perspective and places special emphasis on developing the skills and instincts needed to make sound decisions and become an effective manager. The main components of the course 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.

Taught by Mark Glickman (FAS), Mike Parzen (HBS), and Kevin Rader (FAS)

Seminar I (2 Weeks)

expand_more

Leadership, Innovation, and Change

An emphasis on data analytics and algorithms at the center of an enterprise also means that leaders will have to drive both innovation and large-scale organizational change. This course will focus on the leader’s role in both executing their current strategy better than their competitors as well as their role in shaping strategic innovation. We employ the congruence model that links strategy to execution through alignment of culture, people, tasks, structure, and executive leadership. We also explore the inertial characteristics of aligned organizations and the strategic importance of driving innovation streams. We explore building ambidextrous organizations, organizations that can both exploit their existing strategy as well as explore into new strategic domains. Because ambidexterity requires leaders that can deal with punctuated change and paradoxical strategies, our course concludes with what we know about ambidextrous leadership and leading large system change.

Taught by Michael Tushman (HBS) and Rory McDonald (HBS)

*You must complete Digital Strategy and Innovation before you take this course.

Term 1 Immersion (3 Days)

expand_more

In-Person Immersion at Harvard Business School Campus in Boston

During these in-person experiences, you will meet face to face with your classmates, network with faculty and industry leaders during nightly events, tour the Harvard campus, and participate in hands-on guided learning exercises. You will also use the HBS case method, formulating solutions to real-world business scenarios as a way to understand relevant challenges in the industry. Recent topics of discussion have included reputation systems, data sharing and security, and organizational leadership. Immersion dates are subject to change.

Term 3 (1 Course, 8 Weeks)

expand_more

Operations and Supply Chain Management

Digital technologies and data analytics are radically changing the operating model of an organization and how it connects to its broader supply chain and ecosystem. This course emphasizes managing product availability, especially in a context of rapid product proliferation, short product life cycles, and global networks of suppliers and customers. Topics examined include inventory management, distribution economics, demand forecasting, and supplier management. The course emphasizes the “general manager’s perspective” in supply chains. Cases in the course illustrate that barriers to integrating supply chains often relate to behavioral issues (e.g., misaligned incentives or change management challenges) and operational execution problems that fall squarely in the domain of the general manager.

Taught by Ryan Buell (HBS), Dennis Campbell (HBS), Kris Ferreira (HBS), Jan Hammond (HBS), and V.G. Narayanan (HBS)

*You must complete Foundations of Quantitative Analysis before you take this course.

Term 4 (1 Course, 8 Weeks)

expand_more

Programming and Data Science Systems

Modern business analytics requires executives and managers to be conversant with programming and data architecture. The aim of this course is to provide participants with the fundamental knowledge and practice needed to appreciate the challenges and opportunities related to developing robust and scalable systems that are at the core of business analytics by emphasizing mastery of high-level concepts and design decisions. Through a mix of technical instruction, discussion of case studies, and weekly programming projects, this course empowers participants to make technological decisions even if not technologists themselves. Topics include cloud computing, networking, privacy, scalability, security, and more, with a particular emphasis on web and mobile technologies. Participants emerge from this course with firsthand appreciation of how it all works and all the more confident in the factors that should guide their decision-making.

Taught by Henry Leitner (SEAS) and David Malan (SEAS)

Term 5 (1 Course, 8 Weeks)

expand_more

Data-Driven Marketing         

Marketing has been revolutionized and forever changed by data analytics. What used to be a qualitative and instinct-driven business function (think Mad Men) has now become 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 will examine the ways in which marketing has changed and the new skills and capabilities needed to succeed in this function.

Taught by Sunil Gupta (HBS), Ayelet Israeli (HBS), and David Parkes (FAS)

*You must complete Digital Strategy and Innovation, Programming and Data Science Systems, and Foundations of Quantitative Analysis before you take this course.

Seminar II (2 Weeks)

expand_more

Leadership and People Analytics

People analytics is designed to help practitioners use data to improve people-related decisions. Participants will build hands-on skills to analyze data in ways that complement the frameworks and intuitions they would normally use to guide their managerial actions on people issues. At a deeper level, students in any job, organization, or industry context will sharpen their ability to think critically through the lens of rigorous analytics. Anchored in data, this course will equip participants with an analytic approach to diagnosing the varied forces that influence individual, team, and organizational performance, leading to more effective interventions and actions. While developing analytic skills and trying out tools and techniques, participants will come to appreciate the opportunities, limits, and tensions involved in using data analytics to inform people issues, while simultaneously gaining deeper insight into the substance of the business issues in question.

Taught by Jeff Polzer (HBS)

*You must complete Foundations of Quantitative Analysis, and Leadership, Innovation, and Change before you take this course.

Term 6 (1 Course, 8 Weeks)

expand_more

Data Science Pipeline and Critical Thinking

Ultimately, business analytics is about using data, analytics, and algorithms to make prescriptive predictions about future events and decisions. This course will take a holistic approach to helping participants understand the key factors involved, from data collection to analysis to prediction and insight. Projects will give students hands-on experience developing and running a data science pipeline to ensure that the correct business predictions are being made. Emphasis will be on merging technical skills with critical thinking to ensure that robust data science pipelines are being created for business benefit.

Taught by Joe Blitzen, Iavor Bojinov, Srikant M. Datar, and Hanspeter Pfister

*You must complete Digital Strategy and Innovation, Operations and Supply Chain Management, Programming and Data Science Systems, and Foundations of Quantitative Analysis before you take this course.

Term 6 Immersion (3 Days)

expand_more

In-Person Immersion at Harvard Business School Campus in Boston

During these in-person experiences, you will meet face to face with your classmates, network with faculty and industry leaders during nightly events, tour the Harvard campus, and participate in hands-on guided learning exercises. You will also use the HBS case method, formulating solutions to real-world business scenarios as a way to understand relevant challenges in the industry. Recent topics of discussion have included reputation systems, data sharing and security, and organizational leadership. Immersion dates are subject to change.

Why HBAP?

The comprehensive HBAP curriculum will prepare you to

  • speak the language of data scientists;
  • leverage data and analytics to drive strategy and innovation across the firm;
  • gain competitive advantages in a data-centric world;
  • use data to clarify ambiguity and take advantage of economic opportunities;
  • apply data-driven strategies to effectively lead organizational change and inform managerial practices;
  • use data for predictive decision-making; and
  • understand basic programming, data architecture, and quantitative analysis.

“I’m able to communicate or be an intermediary for both information technology departments and management; I can find opportunities for further reporting or enhanced current reports; and I can identify where reports may be misleading or have some miscalculations. Prior to HBAP, I wouldn’t have been able to do any of this.”

– Ruby Arce, HBAP ’21

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