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LinkedIn Learning

Predictive Analytics Essential Training for Executives

via LinkedIn Learning

Overview

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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