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 SpecialistAdd Data Science to your career tool kit.
10 weeks, online
6-8 hours per week
US$2,850 or get US$285 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 Data Science: Bridging Principles and Practice starting on May 25, 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 this program is the first step in your journey to alumni benefits.
Learn More
In this program, you will be introduced to the basics of statistics and analytics in order to build a foundation in data science. You will acquaint yourself with the tools of analytics, explore the business applications of data concepts and tools, and develop the language and skills to work effectively with your data team. By the end of the program, you will be prepared to do the following:
This program is for mid-career managers who want to upskill, C-suite professionals that make impactful organizational decisions, and executives who want to develop their career in a fast-growing field.
While there are no formal prerequisites such as coding knowledge, having an aptitude for quantitative concepts is important.
As pre-term work and in week 1, there will be a review of basic mathematical and statistical concepts such as mean, standard deviation, graphs, histograms, and linear and logarithmic functions. In addition, there will be a weekly 'prep session' to introduce key concepts from the next module that participants may want a refresher on. To gain true literacy in data science, be prepared to get dirty in the data and embrace some math and stats. We'll fully support you along the way.
As you work through the hands-on modules, you will gain meaningful business insights from the data and example cases derived from a broad sampling of industries.
We’ll introduce the foundational concepts behind data science and analytics before exploring the fundamentals of data.
Learn the definitions of key survey terms as well as methods that use sampling to analyze the pros and cons of business decisions through the exploration of sampling, type I and type II errors, and control limits.
Making data-driven business decisions relies on well-articulated hypotheses that lend themselves to statistical tests. We’ll cover the foundations of this approach, including statistical comparisons, confidence intervals, and margins of error.
We’ll explore the most common linear and curved patterns and understand different ways to fit data to linear models. A central application will be understanding market demand, price setting, and elasticities.
Simple regression analyses are at the heart of more elaborate data-driven business decision making. We’ll focus on understanding how these models are used, the assumptions that make their use valid, and how to leverage these models to make better business decisions.
Build on the basics to define the multiple regression model and explore different use cases.
We’ll demystify machine learning by mastering the fundamentals and studying different applications.
With the fundamentals and some of the most common tools under our belts, we’ll dive deep into the competencies that define effective data science teams and show you how to build a data-driven culture in your organization. We will stress common pitfalls and strategies to work effectively with data scientists.
We’ll introduce the foundational concepts behind data science and analytics before exploring the fundamentals of data.
Simple regression analyses are at the heart of more elaborate data-driven business decision making. We’ll focus on understanding how these models are used, the assumptions that make their use valid, and how to leverage these models to make better business decisions.
Learn the definitions of key survey terms as well as methods that use sampling to analyze the pros and cons of business decisions through the exploration of sampling, type I and type II errors, and control limits.
Build on the basics to define the multiple regression model and explore different use cases.
Making data-driven business decisions relies on well-articulated hypotheses that lend themselves to statistical tests. We’ll cover the foundations of this approach, including statistical comparisons, confidence intervals, and margins of error.
We’ll demystify machine learning by mastering the fundamentals and studying different applications.
We’ll explore the most common linear and curved patterns and understand different ways to fit data to linear models. A central application will be understanding market demand, price setting, and elasticities.
With the fundamentals and some of the most common tools under our belts, we’ll dive deep into the competencies that define effective data science teams and show you how to build a data-driven culture in your organization. We will stress common pitfalls and strategies to work effectively with data scientists.
Note: In order to help you explore some of the hands-on techniques that lead directly to making better data-driven decisions, there will be two weeklong learning labs that provide an opportunity to dig deeper into the data. This extends the program to a total of 10 weeks.
Preview Program For FreeDuring this ten-week online journey, you’ll connect directly with UC Berkeley Executive Education's faculty, industry leaders and peers from every corner of the globe. Taking a rigorous, hands-on approach, you’ll analyze data sets using Jupyter Notebook, an interactive open-source platform we will use for computational analysis. While the curriculum is pre-determined, this is an agile learning experience and there may be dynamic opportunities that present themselves based on real-world happenings.
UC Berkeley Executive Education’s faculty members have built strong relationships with industry, including many of the top organizations in and around Silicon Valley. The program's content is either inspired by or directly derived from research and applications from companies that include:
Note: All product and company names are trademarks™ or registered® trademarks of their respective holders. Their use does not imply any affiliation with or endorsement by them.
Since every company is a data company and every organization can benefit from improving its data literacy, we will explore examples from a range of industries, including:
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STEVE TADELIS
Professor of Economics and Sarin Chair in Leadership and Strategy, Berkeley Haas
An expert in e-commerce and the economics of the internet, Prof. Tadelis has extensive experience in the field, including a position as senior director and distinguished economist at eBay (2011–13) and vice president of economics and market design at Amazon (2016–17). His current areas of research include the economics of incentives and organizations, industrial organizations, game theory, and microeconomics. Prior to his position at Berkeley Haas, Prof. Tadelis was assistant professor at Stanford University.
He holds a BA in economics from the University of Haifa, an MSc in economics from Techion Israel Institute of Technology, and a PhD in economics from Harvard University.
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SHACHAR KARIV
Benjamin N. Ward Professor of Economics, Berkeley Haas
Former Chair of the Department of Economics and Faculty Director of the Experimental Social Science Lab (Xlab), Prof. Kariv is an expert in behavioral and experimental economics, focused on individuals’ financial and non-financial decisions. He is cofounder and chief scientist at Capital Preferences and has been a visiting professor at Stanford University, Princeton University, University of Oxford, and University of Cambridge among others.
He holds a BA in economics from Tel Aviv University and an MA and a PhD in economics from New York University.
Enrolling in the Data Science 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.
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.
Preview Program For FreeNote: 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.
Flexible payment options available.