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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$25 (USD)
GSA: $18.25 USD
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Full Course Details
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
- 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.