Introduction to Artificial Intelligence

Illinois places AI concepts in a historical and decision-making context. Machine-learning basics lead into deep learning, generative AI and questions about future systems. It suits learners who want more conceptual depth than a tool demonstration and are prepared to separate established capabilities from predictions about artificial general intelligence.

What you will learn

• Trace major developments in artificial intelligence.
• Compare machine learning and generative-model concepts.
• Evaluate future-facing claims and decision-making implications.

Who this suits

Beginners interested in AI foundations and executive decision-making, with time for a multiweek conceptual course rather than a brief product tutorial.

Before you enroll

Check an AI system’s output against evidence and a clear task requirement. Use fictional or public data for exercises, consider privacy and bias, and distinguish a useful demonstration from reliable performance in production. Accounts, usage limits and subscription features vary across tools; review current terms before depending on a particular feature.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Provider access terms can change; review them before paying.

Put it into practice

Choose a fictional AI proposal and separate its current capabilities from its future assumptions. Identify evidence needed to assess the proposal and a decision that should remain reviewable.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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