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Introduction to Artificial Intelligence

By Sophia

About Course

Introduction to Artificial Intelligence provides a foundational understanding of how intelligent systems work, how machines learn from data, and how AI is applied in real-world industries.


The course explores the history of AI, core concepts such as data, algorithms, and models, and the differences between AI, Machine Learning, and Deep Learning. Learners will understand how machine learning models are trained, evaluated, and deployed.


The course also introduces neural networks, activation functions, Convolutional Neural Networks (CNNs), and key ethical considerations including bias, privacy, transparency, and the future of work.

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What Will You Learn?

  • Define Artificial Intelligence and explain its evolution.
  • Differentiate between Narrow AI and General AI.
  • Explain the relationship between AI, Machine Learning, and Deep Learning.
  • Identify structured and unstructured data.
  • Understand how algorithms and models work in AI systems.
  • Describe supervised, unsupervised, and reinforcement learning.
  • Explain how neural networks process information.
  • Identify common activation functions such as ReLU, Sigmoid, and Softmax.
  • Understand the machine learning lifecycle from data collection to deployment.
  • Evaluate model performance using accuracy, precision, recall, and F1 score.
  • Understand how CNNs are used in image processing.
  • Recognize ethical concerns including bias, privacy, and transparency.

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