The Data Science Playbook for Private Equity and Venture Capital

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Howard Friedman

44:22

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01 - Introduction

01 - What is the data science playbook.mp4

00:43

02 - What you should know for this course.mp4

02:19

02 - 1. Why Data Science Now

01 - Recent changes in data science.mp4

04:00

02 - Data science for private equity and venture capital.mp4

02:41

03 - Barriers to implementing data science.mp4

04:13

03 - 2. Data Science Steps for Private Equity

01 - Data science in the private equity lifecycle.mp4

02:41

02 - Early success with data science.mp4

02:42

03 - Using data science to enhance deal sourcing.mp4

04:48

04 - Using data science to enhance due diligence.mp4

03:24

04 - 3. Data Science Postacquisition Playbook

01 - Developing a data science playbook for portfolios.mp4

02:07

02 - Which portfolio companies will benefit from data science.mp4

03:47

03 - Which departments will benefit from data science.mp4

02:22

05 - 4. Data Science Projects and Machine Learning Applications

01 - Utilizing supervised machine learning applications.mp4

03:00

02 - Utilizing unsupervised machine learning applications.mp4

02:51

06 - Conclusion

01 - Next steps.mp4

02:44

Description

Over the last few years, the field of data science has made rapid advances and spawned radical new shifts in how everyday business is designed to function. This course covers many of the key considerations for systematically using data science to drive growth in private equity and venture capital firms.

Join data scientist and Columbia University professor Howard Friedman for an overview of the data science lifecycle, specifically, how it plays out in finance from exploration and due diligence to post-acquisition value creation. Learn about the steps a private equity and venture capital firm can take to start leveraging data science across their portfolios by creating a data science playbook. By the end of this course, you’ll be equipped with new skills to identify key opportunities for data science within a portfolio and recognize when and how to apply data science methods to gather insights from specific companies.

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Howard Friedman

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.