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Practical Experimentation in Data Science

This course equips data scientists with a hands-on, practical skillset for designing and running experiments. Rather than focusing on a specific experimental design, the course focuses on the practicalities of how to make experiments work within a business, how to ensure they can be used to influence decisions, and how to engage in programmatic (rather than one-off) testing. Learners will leave with both understanding of cutting-edge experimentation methods, as well as the real-world ability to apply them in their current business or organization.

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Eric Weber
Senior Director: Experimentation & Inference, Data Engineering and Data Platform at Stich Fix
Real-world projects that teach you industry skills.
Learn alongside a small group of your professional peers
Part-time program with 2 live events per week:
Next Cohort
February 27, 2023
4 weeks
US$ 400
or included with membership

Course taught by expert instructors

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Eric Weber

Senior Director: Experimentation & Inference, Data Engineering and Data Platform at Stich Fix

Eric Weber has 15 years’ experience working in and teaching others about data. Eric is currently Senior Director: Experimentation & Inference, Data Engineering and Data Platform, at Stitch Fix, following previous stints at LinkedIn, CoreLogic, and Yelp. Eric loves working with people and data, educating others about data’s value and helping people excel in technical roles. Eric’s strength in teaching others was developed through his academic career as an assistant professor.

Eric holds a PhD and Masters in mathematics from ASU, a Masters in Business Analytics from University of Minnesota, and is currently completing an executive MBA at the University of Chicago Booth School of Business.

The course

Learn and apply skills with real-world projects.

Project details coming soon
    • Randomization
    • Replication
    • Reduction of Variance
    Project details coming soon
      • Identifying gaps/opportunities where cost of running an experiment is worth the potential choice to make
      • Establishing a hypothesis
      • Selecting the right time to run an experiment
      • Documenting your experiment
      • Cross-functional stakeholder engagement
      • Running the experiment
      • Concluding the experiment and recording decisions
      Project details coming soon
        • Understanding organizational structure and identifying allys vs. blockers
        • Organizational culture of experimentation
        • Aligning with the incentives and goals of others
        Project details coming soon
          • Understanding experimentation platforms
          • Building experimentation partnerships inside the company
          • Fostering a culture of experimentation
          • Documenting records of experimentation

          Real-world projects

          Work on projects that bring your learning to life.
          Made to be directly applicable in your work.

          Live access to experts

          Sessions and Q&As with our expert instructors, along with real-world projects.

          Network & community

          Core reviews a study groups. Share experiences and learn alongside a global network of professionals.

          Support & accountability

          We have a system in place to make sure you complete the course, and to help nudge you along the way.

          This course is for...

          Data Analysts/Business Analysts looking to further their career into Data Science

          Other software engineers seeking to transition into data science and statistics related roles


          Knowledge of foundational statistics and modeling methods (as covered in CoRise Applied Statistics for Data Science)

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