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LinkedIn Learning

Ethics and Law in Data Analytics

via LinkedIn Learning

Overview

Analytics and AI are powerful tools that have real-word outcomes. Learn how to the practical, ethical, and legal frameworks to be an effective analytics professional.

Syllabus

Welcome
  • Welcome
Module 1: Data, Ethics, and Law
  • Data, ethics, and law
  • Designing the data revolution
  • The age of big data
  • Ethical foundations: Part 1
  • Ethical foundations: Part 2
  • Ethical foundations: Part 3
  • Law, analytics, and society
  • Different types of law
  • IRAC analysis
  • Subjective to objective
  • A Data oath
  • IRAC application
  • Explore the compassions data set: Part 1
  • Explore the compassions data set: Part 2
  • Explore the compassions data set: Part 3
Module 2: Data, Individuals, and Society
  • Data, individuals, and society
  • Bias in data processing: Part 1
  • Bias in data processing: Part 2
  • Legal concerns for equality
  • Bias and legal challenges
  • Consumers and policy
  • Employment and policy
  • Education and policy
  • Policing and policy
  • Best practices to remove bias
  • Descriptive analytics and identity
  • Privacy, privilege, or right
  • Privacy law and analytics
  • Negligence law and analytics
  • Power imbalances
  • IRAC application
Module 3: Data Ethics and Law in Business
  • Data ethics and law in business
  • Handling consumer data
  • Handling employee data
  • Ethics in hiring with big data
  • Digital market manipulation
  • The evolution of privacy and technology
  • Data privacy and security best practices
  • GDPR
  • GDPR, big data, and AI
  • IRAC application
  • The ethics and variables of recidivism
Module 4: Artificial Intelligence and Future Opportunities
  • AI and future opportunities
  • From analytics to AI
  • AI design principles
  • Example autonomous cars
  • Values like ours
  • Why XAI
  • XAI the issues
  • XAI complex algorithms
  • XAI or GAI
  • Algorithms and accountability
Conclusion
  • Wrap up

Taught by

Microsoft General Technical Skills

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4.7 rating at LinkedIn Learning based on 372 ratings

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