Introduction to Artificial Intelligence (AI)

IBM introduces AI through applications, core terminology and the relationship between machine learning, deep learning and neural networks. Business and career examples sit alongside questions about responsible use. It suits learners who want a broad foundation before choosing a technical specialization and who want to discuss a proposed AI application with clearer expectations.

What you will learn

• Distinguish AI, machine learning and deep learning.
• Explore applications and generative AI concepts.
• Evaluate ethical questions in a proposed AI use case.

Who this suits

Beginners, students and working professionals interested in AI foundations; the provider identifies a broad audience rather than requiring programming experience.

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 organizational problem and describe an AI-assisted approach. Identify the needed information, a likely limitation and evidence that would be required before using its output.

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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