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Introduction to Artificial Intelligence - CS 230

Introduces AI concepts, search, classification, machine learning basics, neural networks, applications, limitations, and responsible AI.

Study Tools

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Study guides

7

7 Limitations and Responsible AI

Learn how AI limitations can lead to harm and how responsible design, evaluation, oversight, and monitoring can help manage those risks.
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5 Neural Networks

Learn how neural networks are structured, how they learn from examples, where they are used, and why their predictions and limitations need careful evaluation.
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6 AI Applications

Explore how AI supports tasks across industries, how AI systems are developed and evaluated, and what safeguards help address their limitations and real-world risks.
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3 Classification Fundamentals

Learn how classification models use labeled examples and features to predict categories, and how to evaluate their predictions with a test set and performance measures.
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1 Introduction to Artificial Intelligence

Learn what artificial intelligence systems do, how common AI approaches work, and what their capabilities and limitations mean.
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2 Problem Solving and Search

Learn how to represent search problems, how common search algorithms explore possible paths, and how to choose a strategy based on costs, guidance, solution quality, and resource limits.
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4 Machine Learning Basics

Learn how machine learning models learn from data, how to choose an evaluation approach, and how to avoid common pitfalls when developing and assessing models.
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Quizzes

7

2 Problem Solving and Search

A medium-difficulty quiz on representing search problems, exploring state spaces, and choosing search strategies.
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6 AI Applications

A medium-difficulty quiz on AI applications, system development, evaluation, and responsible use.
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4 Machine Learning Basics

A medium-difficulty quiz on machine learning concepts, data preparation, and model evaluation.
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1 Introduction to Artificial Intelligence

A medium-difficulty quiz applying foundational concepts of artificial intelligence, including system types, learning, and responsible use.
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3 Classification Fundamentals

A medium-difficulty quiz on classification concepts, features and labels, and evaluating classifier performance.
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5 Neural Networks

A medium-difficulty quiz on neural network components, learning, applications, and limitations.
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7 Limitations and Responsible AI

A medium-difficulty quiz on AI limitations, fairness, privacy, transparency, safety, and responsible oversight.
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Flashcards

7

5 Neural Networks

Review neural network components, how they learn, common uses, and important limitations.
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7 Limitations and Responsible AI

Learn key limitations of AI and practical principles for making its design and use safer, fairer, and more accountable.
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4 Machine Learning Basics

Learn core machine learning concepts, learning approaches, dataset splits, and common evaluation pitfalls.
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2 Problem Solving and Search

Review how search problems are represented and how uninformed and informed strategies explore paths toward a goal.
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6 AI Applications

Learn how AI is applied, developed, evaluated, and used responsibly across real-world settings.
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1 Introduction to Artificial Intelligence

Review core artificial intelligence concepts, system types, and important limitations.
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3 Classification Fundamentals

Learn how classification models use labeled examples and features, and how to interpret common classification metrics.
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