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LinkedIn Learning

Predictive Analytics Essential Training for Executives

via LinkedIn Learning

Overview

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Learn how to hire and manage data science professionals and transform your business with effectively deployed advanced analytics.

Syllabus

Introduction
  • Speak the language of data scientists
1. Getting Serious about Analytics
  • Analytics is about making decisions
  • Propensity scores and business problems
  • The unintended consequences of proof of concept projects
  • Why deployment, not insight, is the primary goal
  • Analytics as a profit center
2. Hiring for Analytics
  • Data science job requirements and problems they can create
  • Growing a data science team organically
  • Data scientists both with and without vertical industry experience
  • The importance of subject matter expertise to modeling
  • CRISP-DM: Established process of producing predictive models
  • Traits of top performing data scientists
3. What to Consider before Buying Software
  • Analytics and machine learning software options
  • Specific data prep for each project
  • Citizen data scientists and self service analytics
  • AutoML and self-service analytics: Emerging technologies
  • Explainable AI and interpretable machine learning
4. Organizational Structure
  • Analytics project management
  • The career path of the data scientist
  • Who data scientists should report to
  • The CAO: Organizational structure from a senior executive POV
Conclusion
  • Next steps

Taught by

Keith McCormick

Reviews

4.6 rating at LinkedIn Learning based on 376 ratings

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