Berkeley Program on Data Science & Analytics

The Berkeley Program on Data Science and Analytics (BPDSA) is a six-month learning journey into the world of applied data science and analytics. The program leverages 5 modules, three on-campus and two online. The program provides you with tools to build and lead data science teams through data-driven decision-making. You will learn how to promote a data-driven culture, how to translate business problems, and how to lead a team with a diverse set of skill sets towards solving these problems. Participants graduate with Certificate of Excellence in Data Science and Analytics and earn Alumni Benefits.

Berkeley Program on Data Science & Analytics (BPDSA)

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Program Highlights

Note; Final schedule subject to change*

Program Benefits

Develop skills to be a data-driven leader

Immersive modules at Berkeley

World-class Faculty and Practitioners

Project work

Alumni Benefits

Alumni Benefits

Plug into the Berkeley Haas Alumni Network and engage with over 41,000 Berkeley Haas Alumni across the world. Build your professional brand, connect with your network, advance you career or plan for the future.


Data and

  • Decision Analysis - Decision trees, Backward induction
  • Decision making under uncertainty
  • Statistical methods to solve business problems
  • Effective data visualization
  • Game Theory

Economic Analysis for
Decision Making

  • Economic Costs
  • Demand Estimation and Pricing Strategies
  • Market Segmentation
  • Tools for competitive advantage
  • Designing effective incentives

Inference and

  • Sampling, Surveys and Biases
  • Estimating parameters
  • Statistical Tests
  • Micro-econometric data analysis
  • A/B Testing
  • Experimentation and Evaluation

Forecasting and

  • Predictive analysis
  • Time Series forecasting and analysis
  • Linear, Multiple and ANOVA Regression Models
  • Regression Diagnostics

Machine Learning and
Artificial Intelligence

  • Trees, Random Forest and Boosting
  • Comparing Machine Learning Approaches: Neural Networks, Support Vector Machines, Trees, Multivariate adaptive regression splines, k-NN
  • Lasso and Linear Regularization
  • Leverage ML and AI for business insights from big data
  • Tools for Supervised Learning Methods
  • Tools for Unsupervised Learning Methods

Building a Data
Science Team

  • Mapping of resources from expert backgrounds to solve problems
  • Build a data science team
  • Organizational Structure: Centralized, Distributed or Hybrid
  • Design a tech eco-system which complements the data science team
  • Develop a data-driven culture


From session-to-session, participants will apply classroom lessons to a capstone project that evolves throughout the course. They are organized in groups or they can work individually on an opportunity or problem they are interested in.



Hear from leading practitioners in the Silicon Valley innovation ecosystem and conduct site visits to startups, accelerator labs and innovative enterprise firms.

Past guest speakers have included:

Past guest speakers

Past site visits have Included:

Past site visits
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Faculty Directors

Shachar Kariv

Shachar Kariv

Faculty Director

Sachar Kariv is the Benjamin N. Ward Professor of Economics and former Department Chairperson, and Faculty Director of Berkeley’s Experimental Social Science Laboratory (XLab). Sachar is also the Co-Founder and Chief Scientist of Capital Preferences, where he applies his research on individual saving, investment and insurance choices to help clients make better decisions about how to design and market products and services, and improve customer acquisition, relationship, and retention.

Steve Tadelis

Steve Tadelis

Co - Faculty Director

Steve Tadelis is the James J. and Marianne B. Lowrey Chair in Business and Professor of Economics, Business and Public Policy at Haas. Steve was a Senior Director and Distinguished Economist at eBay Research Labs (2011-2013) and Vice President of Economics and Market Design at Amazon (2016-2017) where he applied economics research tools to a variety of product and business applications, working with technologists, machine learning scientists, and business leaders. He continues to advice Amazon part-time as an Amazon Economist Fellow.

Note: Program faculty is subject to change

Participant Profiles

This program is ideal for managers and leaders who aim to leverage data analytics in their decision making processes and to build data science teams in their organizations.


Past Participant Profiles

Diversity in multiple aspects is an important part of the learning experience. The participant mix reflects diversity across functions, industries, backgrounds, organizations and life experiences.




Work Experience



Geographic Locations

Geographic Location


Note; The above data is across previous cohorts

Participant Testimonials

Berkeley program on data Science & Analytics - Peers & Networking by Eruditus Executive Education

Berkeley Program on Data Science & Analytics - Key Takeaways by Eruditus Executive Education

Berkeley Program on Data Science & Analytics - Reasons to choose the program by Eruditus Executive Education

Berkeley program on data Science & Analytics - Guest Speakers & Industry site visits by Eruditus Executive Education

Berkeley Program on Data Science & Analytics - Faculty by Eruditus Executive Education


Module Date Location
Module 1 Mar 02–06, 2020 Berkeley Campus
Module 2 Mar 23, 2019–Apr 30, 2020 Online
Module 3 May 11–15, 2020 Berkeley Campus
Module 4 Jun 15–Aug 7, 2020 Online
Module 5 Aug 31–Sep 4, 2020 Berkeley Campus


  • Inclusions: Program Materials, Coffee Breaks, Lunches and Select Dinners
  • Exclusions: Travel Costs and Accommodation

Application Deadlines and Fees

Round Date Application Fees
Round 1 21st Oct, 2019 USD $300
Round 2 25th Nov, 2019 USD $400
Round 3 23rd Dec, 2019 USD $500
Round 4 27th Jan, 2020 USD $600
Program Fees: USD $29,000