Coursera’s Machine Learning for Everyone Fulfills Unmet Training Needs

Coursera’s Machine Learning for Everyone Fulfills Unmet Training Needs

Coursera’s Machine Learning for Everyone (free access) fulfills two different kinds of unmet learner needs, for both the technology side and the business side, covering state-of-the-art techniques, business leadership best practices, and a wide range of common pitfalls and how to avoid them.


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Unmet Training Needs Fulfilled by Coursera’s
“Machine Learning for Everyone”

Coursera’s Machine Learning for Everyone (free access) fulfills two different kinds of unmet learner needs. It’s a conceptually-complete, end-to-end course series – its three courses amount to the equivalent of a college or graduate-level course – that covers both the technology side and the business side. While fully accessible and understandable to business-level learners, it’s also also vital to data scientists and budding technical practitioners, since it covers:

  • The state-of-the-art techniques
  • The business leadership best practices
  • A wide range of common pitfalls and how to avoid them
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1) A comprehensive go-to for BUSINESS-SIDE learners – by covering the following:

  • ML project leadership (management process)
  • ML algorithms: substantive yet accessible coverage
  • Data preparation

2) Need-to-knows for EVERYONE in ML – both business-side learners and technical practitioners – by also covering the following:

  • ML ethics: risks to social justice, equitable models, machine bias, etc.
  • Business-oriented performance metrics
  • Uplift modeling (aka persuasion modeling)
  • Major pitfalls, in-depth:
    • P-hacking
    • Overfitting
    • The accuracy fallacy
    • Presuming causation from correlations
    • Serious problems with hyping ML as “AI”

This checklist illustrates the unique contribution of this curriculum:

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More information about “Machine Learning for Everyone”:

 
Click here for free enrollment: Machine Learning for Everyone

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