🎓 Lesson 43: What Is Overfitting in Machine Learning? Lesson Objective: To help learners understand what overfitting means in machine learning, why it happens, how
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🎓 Lesson 41: What Are the Ethical Considerations When Developing AI Systems? 🔍 Lesson Objective: To help learners understand the ethical principles, challenges, and responsibilities
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🎓 Lesson 40: How Is AI Applied in Urban Planning and Smart Cities? 🔍 Lesson Objective: To help learners understand how AI technologies are used
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Lesson 39: How Does AI Contribute to the Optimization of Manufacturing Processes? Lesson Objective: To help learners understand how AI is being used to streamline
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🎓 Lesson 15: Training, Testing, and Evaluating AI Models Lesson Objective: To help learners understand how AI models are trained, validated, and tested using data
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🎓 Lesson 13: Reinforcement Learning Lesson Objective: To introduce learners to Reinforcement Learning (RL) — how it works, where it’s used, and how it differs
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🎓 Lesson 11: Supervised Learning Lesson Objective: To help learners understand what Supervised Learning is, how it works, and where it is commonly used in
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🎓 Lesson 9: Natural Language Processing (NLP) Lesson Objective: To help learners understand what Natural Language Processing (NLP) is, how it works, and how it’s
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🎓 Lesson 8: Deep Learning – Going Deeper Into AI Lesson Objective: To help learners understand what Deep Learning is, how it builds upon neural
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🎓 Lesson 7: Neural Networks and How They Work Lesson Objective: To help learners understand what Artificial Neural Networks (ANNs) are, how they are inspired
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