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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.

Key Benefits

  • Develop skills to be a data-driven leader: Acquire critical skills to leverage data and analytics in order to drive strategy and innovation across the organization; Gain in-depth understanding in statistical methods for decision-making, Experiments, A/B Testing, Predictive Analytics, AI/ML tools for business insights, assembling a data science team, to name a few.
  • Immersive modules at Berkeley: Learn in the Silicon Valley innovation ecosystem, an unparalleled learning lab for innovation unlike anywhere in the world.
  • World-class Faculty and Practitioners: The program is taught by world leading experts who are Berkeley Faculty, many of who have engaged with some of the largest data-driven companies like eBay, Amazon and more.
  • Project work: Benefit from experiential sessions which combine theory, real life case studies and project work to help you gain practical perspectives. Work on projects to fortify the tools, frameworks and key aspects learned in the program.
  • Alumni Benefits: Participants graduate with Certificate of Excellence in Data Science and Analytics and earn Alumni Benefits and be a part of network of 41,000+ alumni across the globe.

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COVID-19

We are closely monitoring the ongoing COVID-19 pandemic. As the situation continues to change rapidly, the health, safety and well-being of the entire community is of paramount importance to us. We are committed to providing you with the most current information available about the program. Our aim is to ensure the academic integrity and learning experience of the program that you are applying for.

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.   Pre-requisites:

  • A minimum of 10 years of work experience
  • Fluency in written and spoken English
  • No coding experience required
  • INDUSTRY

    INDUSTRY
  • GOEGRAPHIC LOCATION

    GOEGRAPHIC LOCATION
  • EXPERIENCE

    EXPERIENCE
  • ORGANISATIONS

    ORGANISATIONS
  • FUNCTIONS

    FUNCTIONS

Program Curriculum

  • Data and Decisions

    • 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 measurement

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

    • 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
Note: The list of topics is not exhaustive and is subject to change.

Faculty Directors

  • Shachar Kariv

    Shachar Kariv

    Faculty Director

    Shachar Kariv is the Benjamin N. Ward Professor of Economics, and former Chair of the Department of Economics and Faculty Director of Experimental Social Science Laboratory (Xlab). His research in behavioral and experimental economics provides novel tools for understanding individual preferences and attitudes towards risk and time, which inform nearly all aspects of decision-making. The research has uncovered valuable new insights about individuals’ financial and non-financial decisions; these insights enable clients to make better decisions about how to design and market their products and services, and improve client acquisition, relationship, and retention.

    His academic experience includes visiting professorship positions at Stanford University, Princeton University, University of Oxford, University of Cambridge, the European University Institute, the Norwegian School of Economics, among others. Among his awards, Shachar was awarded a Sloan Fellowship and received special recognition for his distinguished excellence in teaching from UC Berkeley Division of Social Sciences and the Haas School of Business. Professor Kariv is also a Co-Founder Chief Scientist at Capital Preferences, a company revolutionizing enterprise investment advice, lending, insurance and talent market solutions. The breakthrough “Economic Fingerprint” technology and methodology created by Capital Preferences aims to solve the biggest challenges facing the most dynamic industries.

  • Steve Tadelis

    Steve Tadelis

    Co - Faculty Director

    Steve Tadelis holds the Sarin Chair in Strategy and Leadership and is a Professor of Economics, Business and Public Policy at Haas School of Business, University of California, Berkeley. Steve previously held the James J. and Marianne B. Lowrey Chair in Business (2016-2019) and the Joe Shoong Chair in International Business (2015-2016) and served as the Associate Dean for Strategic Planning (2006-2009) at the Haas School of Business. Prior to starting his position at Berkeley Haas, Steve was an Assistant Professor at Stanford University for eight years. While on leave from Berkeley, Steve held positions as 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 economic research tools to a variety of product and business applications, working with technologists, machine learning scientists, and business leaders. He continues to advise Amazon part-time as an Amazon Scholar. Steve’s current areas of research are e-commerce, industrial organization, procurement contracting, and market design.

Faculty

*PROGRAM FACULTY MAY CHANGE.

Dates & Fees

Dates Length Location Tuition Fees
TBD TBD TBD TBD
Deadline Application Fees
TBD TBD TBD

Note:

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

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FAQs

What is Berkeley Data Science & Analytics Program?

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 provides participants with tools to build and lead data science teams through data-driven decision-making.

Who should attend this program?

The Berkeley Program on Data Science and Analytics (BPDSA) is ideal for managers and senior leaders across industries who aim to leverage data analytics in their decision-making processes and to build data science teams in their organizations.

How is the program structured?

The Data Science and Analytics program has 3 on-campus modules at Berkeley and 2 online modules. The curriculum includes: Economic Analysis for Decision Making, Data and Decisions, Inference and measurement, Forecasting and trends, Machine Learning and Artificial Intelligence, Assembling a Data Science Team.

Will I receive a certification after completing this program?

Upon completion of the Berkeley Program on Data Science and Analytics, participants will be awarded the ‘Certificate of Excellence in Data Science and Analytics Leadership’ from Berkeley Haas Executive Education.

How can I apply for this program?

Applications to the Berkeley Data Science and Analytics program can be made online and should include an updated resume/ LinkedIn profile as well as professional references. The application fees vary by rounds - applying earlier help your chances of being accepted into the program.