Introduction to AI & Machine Learning eLearning

Discover AI & ML: The New Age of Technology

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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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