Decoding AI: A Deep Dive into AI Models and Predictions

This course is part of Understanding Data: Navigating Statistics, Science, and AI Specialization

Instructor: Elle O'Brien

What you'll learn

  •   Learn key concepts and terminology in artificial intelligence (AI), including machine learning, generative AI, and deep learning
  •   Learn the core components of machine learning systems, including data, models, and evaluation techniques
  •   Recognize why AI systems can fail and identify the kinds of work required to make useful technology
  •   Identify common pitfalls in conversations about AI and recognize conflicts of interest when interpreting claims about AI systems

    • Skills you'll gain

  •   Data Ethics
  •   Artificial Intelligence
  •   Machine Learning
  •   Generative AI
  •   Media and Communications
  •   Predictive Modeling
  •   Data-Driven Decision-Making
  •   Data Analysis
  •   Data Literacy

    • There are 4 modules in this course

    This is the third course in Understanding Data: Navigating Statistics, Science, and AI Specialization, in which you’ll gain a core foundation for statistical and data literacy and gain an understanding of the data we encounter in our everyday lives.

    How Do Machine Learning Systems Work?

    The Limits of Data and Prediction

    How to Have Better Conversations About AI

    Explore more from Machine Learning

    From Data to Decisions: Making Predictions with AI

    Understanding Data: Navigating Statistics, Science, and AI

    From Data to Decisions: Getting Started with AI

    How Science Turns Data Into Knowledge

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