The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.

Courtlyn
Promotion and Events SpecialistBusiness growth through analytical decision-making
June 9, 2022
2 months, online
4–6 hours per week
US$2,600 US$2,288 or get US$260 off with a referral
Our participants tell us that taking this program together with their colleagues helps to share common language and accelerate impact.
We hope you find the same. Special pricing is available for groups.
The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events SpecialistBased on the information you provided, your team is eligible for a special discount, for Business Analytics for Leaders: From Data to Decisions starting on June 9, 2022 .
We’ve sent you an email with enrollment next steps. If you’re ready to enroll now, click the button below.
Have questions? Email us at group-enrollments@emeritus.org.Enrolling in the Business Analytics for Leaders program is your first step toward the Certificate of Business Excellence. You will have access to a private global network of more than 41,000 UC Berkeley alumni in more than 80 countries, along with exclusive benefits available only to UC Berkeley alumni who have completed the Certificate of Business Excellence:
Networking and events
Berkeley resources
News and communication
Note: All benefits subject to change.
Enrolling in this program is the first step in your journey to alumni benefits.
Learn More
This program will position you to:
Today’s business leaders know that analytics is critical to tomorrow’s success. Many have already discovered how data-driven decisions enable stronger business cases and greater agility, while others are behind the curve.
Across every sector, business professionals—including those with no coding or advanced analytics experience—are recognizing the need to develop their data fluency and understand how key technologies such as AI intersect with data analytics. In this program, with the help of hands-on activities, live sessions as well as real-world case studies you will discover how data-driven decisions enable stronger business cases and greater agility.
Data-driven organizations are now 23x more likely to acquire customers, 6x as likely to retain customers and 19x more likely to be profitable.
94% of enterprises say data and analytics are important to their business growth and digital transformation
Businesses are using analytics to increase efficiency, improve customer service, and identify risks and opportunities across all sectors. This program is designed for business professionals who recognize this growing trend and want to use data and analytics techniques to guide strategy at the top levels of their organizations. (No previous coding or advanced analytics experience is necessary.) Business Analytics for Leaders: From Data to Decisions program could be particularly beneficial for those in the following roles:
Mid- to Senior-level Managers who want to drive innovation at their organizations by leveraging data-based decision-making models. Representative roles include:
Senior Executives and Business Heads who want to better understand the business opportunities that analytics enable, as well as regulations related to data protection and privacy implications. Representative roles include:
Consultants who want to provide client solutions based on the latest data and technology. Representative roles include:
Data Analytics and Technology Professionals who want to lay out the roadmap for analytics and AI initiatives for their organization, with an objective of solving key business problems. Representative roles include:
Over the course of two months, you will incrementally build your analytics acumen to better equip you for a rapidly evolving, data-centric world.
From the beginning, this program grounds your understanding of business analytics in the real world by citing actual business cases, not just theoretical applications. In this module we introduce the AI-centric operating model, and how to leverage its four components to achieve scale, scope, and innovation.
This module is all about data: how to access it, process it, transform it, and make it AI-ready. We will also introduce the concept of data visualization and learn some of the best practices for accomplishing it.
In this module you will learn how to exploit patterns in historical data to forecast future events using predictive analytics, a key tool for identifying risks and opportunities. We will also examine the scope of supervised learning in business using several examples.
Continuing our discussion of supervised learning and predictive analytics, in this module we introduce state-of-the-art AI techniques to enable data-driven decision-making.
In this module we switch to unsupervised learning, which can help you group and cluster data more effectively. The wide range of business applications includes everything from customer segmentation to detecting fraudulent transactions.
Here we explore the ways that AI-centric businesses use reinforcement learning for recommender systems, web advertising, stock trading, healthcare, and many other applications. The computer performs a succession of trial-and-error interactions within a dynamic environment to try to determine which approach is best.
In this module we learn how businesses develop experimentation platforms that enable them to run many tests at high velocity, which in turn allows them to learn, adapt, innovate, and make sound business decisions even in times of uncertainty.
We will first discuss some concerns associated with the use of machine learning in prescriptive analytics, and how this might affect our business strategies moving forward. We will then discuss data protection and privacy, which will continue to be an important consideration in the world of Big Data. We will not only present some best practices associated with data protection, but also outline steps for developing a more general data strategy.
From the beginning, this program grounds your understanding of business analytics in the real world by citing actual business cases, not just theoretical applications. In this module we introduce the AI-centric operating model, and how to leverage its four components to achieve scale, scope, and innovation.
In this module we switch to unsupervised learning, which can help you group and cluster data more effectively. The wide range of business applications includes everything from customer segmentation to detecting fraudulent transactions.
This module is all about data: how to access it, process it, transform it, and make it AI-ready. We will also introduce the concept of data visualization and learn some of the best practices for accomplishing it.
Here we explore the ways that AI-centric businesses use reinforcement learning for recommender systems, web advertising, stock trading, healthcare, and many other applications. The computer performs a succession of trial-and-error interactions within a dynamic environment to try to determine which approach is best.
In this module you will learn how to exploit patterns in historical data to forecast future events using predictive analytics, a key tool for identifying risks and opportunities. We will also examine the scope of supervised learning in business using several examples.
In this module we learn how businesses develop experimentation platforms that enable them to run many tests at high velocity, which in turn allows them to learn, adapt, innovate, and make sound business decisions even in times of uncertainty.
Continuing our discussion of supervised learning and predictive analytics, in this module we introduce state-of-the-art AI techniques to enable data-driven decision-making.
We will first discuss some concerns associated with the use of machine learning in prescriptive analytics, and how this might affect our business strategies moving forward. We will then discuss data protection and privacy, which will continue to be an important consideration in the world of Big Data. We will not only present some best practices associated with data protection, but also outline steps for developing a more general data strategy.
Capstone Project - The two-month Business Analytics for Leaders: From Data to Decisions program culminates with a capstone project in which you solve a real-world business problem using an AI-centric operating model.
Download BrochureTo get a clearer understanding of how business analytics actually works in the real world, you will examine several case studies involving these prominent companies:
Explore how LendingClub used supervised learning (or predictive analytics) to predict whether borrowers will repay or default on their loans.
Discover how eBay used prescriptive analytics and experimentation to make strategic decisions for feature implementation.
Explore how Osaro leveraged deep reinforcement learning to enable automation and transform the warehouse market.
Learn how Ant Group built an AI-centric operating model based on analytic approaches to achieve scale, scope, and innovation.
Note: All product and company names are trademarks or registered trademarks of their respective holders. The study of these products and/or companies does not imply any affiliation with or endorsement by them.
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Frederico Finan
Professor, UC Berkeley’s Department of Economics and Haas School of Business
An expert in applied microeconomics, Prof. Finan teaches graduate courses in data analytics in Haas’ Executive MBA Programs. His research uses data analytics to explore the interactions between economic and political forces in developing countries. Typically, this involves working with large datasets and using A/B testing techniques to better incorporate data and empirical evidence into business and policy decision-making.
Prof. Finan has published more than 20 peer-reviewed papers, many in top academic journals such as American Economic Review and the Quarterly Journal of Economics. Other relevant credentials include: Faculty Director of Berkeley’s Center for Economics and Politics; Board Member and Fellow of the Bureau for Research and Economic Analysis of Development (BREAD); and Research Associate at the National Bureau of Economic Research. In 2013, Prof. Finan was awarded an Alfred P. Sloan Research Fellowship.
Prof. Finan has given more than 100 invited presentations on data analytics and other research topics, including recent presentations at the University of Chicago, Harvard University, Stanford University, Yale University, and the World Bank.
Prof. Finan received a PhD in Agricultural and Resource Economics from UC Berkeley in 2006. He was an Assistant Professor of Economics at the University of California, Los Angeles and a Visiting Professor at Stanford University’s Graduate School of Business before returning to UC Berkeley as a faculty member in 2009.
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Demian Pouzo
Associate Professor, Department of Economics, UC Berkeley
A member of UC Berkeley’s faculty since 2009, Prof. Pouzo teaches graduate courses in data analytics in Haas’ Executive Education Programs. In addition to exploring how individuals make decisions under uncertainty, his research focuses on developing tools for machine learning methods, with an emphasis on uncovering patterns that underlie the data.
Prof. Pouzo has published peer-reviewed papers in journals specializing in economics, finance, statistics, and applied mathematics. He is associate editor for the Journal of Econometrics Methods and Journal of Econometrics. Presentations at the University of Chicago, Harvard University, and MIT are among his more than 100 invited presentations on machine learning and other research topics.
Prof. Pouzo received a PhD in Economics from NYU in 2009, under the supervision of Ricardo Lagos, Xiaohong Chen and Tom Sargent (Nobel Prize in Economics 2011).
Get recognized! Upon successful completion of the program, UC Berkeley Executive Education grants a verified digital certificate of completion to participants. Participants must complete 80 percent of the required activities including a capstone project (if any) to obtain the certificate of completion. This program also counts toward a Certificate of Business Excellence.
Download BrochureNote: This program results in a digital certificate of completion and is not eligible for degree credit/CEUs. After successful completion of the program, your verified digital certificate will be emailed to you in the name you used when registering for the program. All certificate images are for illustrative purposes only and may be subject to change at the discretion of UC Berkeley Executive Education.
This program counts toward a Certificate of Business Excellence
Curriculum Days: Two days
Pillar(s): Entrepreneurship & Innovation / Strategy & Management
A UC Berkeley Certificate of Business Excellence gives individuals the opportunity to create a personal plan of study structured by our four academic pillars. Participants will earn a mark of distinction with certification from a world-class university, and enjoy the flexibility of completing the program in up to three years.
Flexible payment options available.