Introduction to AI & Machine Learning eLearning

Discover AI & ML: The New Age of Technology

Overview

This course illuminates the fundamental concepts and key terms of artificial intelligence (AI) and machine learning (ML), empowering you to apply these technologies across diverse real-world applications. Explore the building blocks of AI and ML, and master the essentials of data management to shape the future of innovation.

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Full course details

Course outline

Part 1: Introduction to AI

  • Overview: What is AI and its significance?
  • History: Brief evolution of AI and its modern applications.
  • Ethics: Considerations on AI ethics, bias, privacy, and societal impacts.

Part 2: AI Concepts

  • AGI, ANI, ASI: Explanation of different AI levels and their implications.

Part 3: Machine Learning Basics

  • Goals: Objectives of ML-like prediction and pattern recognition.
  • Types:
    • Supervised Learning: Using labeled data for tasks like classification.
    • Unsupervised Learning: Identifying patterns in unlabeled data.
    • Semi-supervised Learning: Leveraging both labeled and unlabeled data.
  • Reinforcement Learning: Learning from interactions with an environment.

Part 4: Assessment

In this class you will learn how to
  • AI Fundamentals: Basic concepts and significance.
  • AI Ethics: Bias, privacy, societal impacts.
  • AI Levels: AGI, ANI, ASI distinctions.
  • ML Techniques: Supervised, unsupervised, semi-supervised, reinforcement learning.
  • ML Applications: Real-world problem solving.

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