How Artificial Intelligence (AI) Works
This course introduces learners to the foundational concepts behind how artificial intelligence systems work, with a focus on machine learning and deep learning. Learners will explore how AI systems use data, algorithms, and patterns to make predictions and decisions, as well as the differences between supervised learning, unsupervised learning, reinforcement learning, and deep learning. Through practical examples, learners will gain insight into how these approaches power technologies such as email filtering, customer recommendations, image recognition, voice assistants, and autonomous systems.
Course Objectives
Upon completion of How Artificial Intelligence (AI) Works you will be able to:
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Explain how machine learning enables AI systems to learn from data, recognize patterns, and improve performance over time.
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Differentiate between supervised learning, unsupervised learning, reinforcement learning, and deep learning by identifying their purposes and real-world applications.
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Apply knowledge of machine learning methods to classify AI examples and determine which learning approach best fits different scenarios.
Seat Time: 5 min
Catagories: Technology
Keywords: Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Algorithms, Data, Pattern Recognition, Supervised Learning, Unsupervised Learning, Reinforcement Learning Demo This Course
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