Data for Good: Using Data Science in Nonprofits and NGOs

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Martin Kemka

33:51

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01 Introduction

001 Data science isnt just for capitalists.mp4

01:32

02 Data Use Overview

001 How data is used everyday.mp4

02:05

002 Oversight to data use.mp4

01:59

003 Machine learning and data science overview.mp4

03:02

004 Challenge Define machine learning.mp4

00:32

005 Solution Define machine learning.mp4

00:59

03 How the Data for Good Concept Is Applied

001 Application for data for good.mp4

02:14

002 Problems that can be solved.mp4

02:47

003 Research applications.mp4

02:37

004 Decision applications.mp4

02:00

005 Challenge Decision example.mp4

00:26

006 Solution Decision example.mp4

00:48

04 Toolsets for Data for Good Work Done

001 Open source analytics.mp4

02:06

002 Open source presentation.mp4

02:13

003 Challenge Set up a mock project.mp4

00:29

004 Solution Set up a mock project.mp4

00:51

05 Working in Groups

001 Data for good groups.mp4

02:38

002 World discussions.mp4

02:19

003 Challenge Finding a challenge.mp4

00:24

004 Solution Finding a challenge.mp4

00:43

06 Conclusion

001 The next steps for using data for good.mp4

01:07

Description

The revolution in data science has transformed, for better or worse, the way companies do business in the last few decades. But data science isn't just for capitalists. AI is one of the most important forces for change developed in the last century, and we've only begun to recognize its true power and potential. In Data for Good: Using Data Science in Nonprofits and NGOs, Martin Kemka examines how data science and machine learning can be used outside of the for-profit sector. He covers parameters for how data works to influence our world, how the data-for-good concept can be applied, how to determine the best problems to solve with data, and what tools are needed. Martin also provides real-world case studies and challenges to further illustrate the lessons.

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Data Science

Martin Kemka

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Linkedin Learning

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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.