LinkedIn Learning has a broad catalog of AI courses, but course listings are not proof that a course is free to watch. LinkedIn says an active subscription is required; individual access is available through LinkedIn Premium, and some employers or institutions may provide access. A Premium free trial may be available to eligible users, but it converts to paid automatically unless canceled before it ends. Here’s how to find a course that fits and check your access before starting.
Are LinkedIn’s AI courses free?
Not generally. LinkedIn Help says, “To access LinkedIn Learning courses, you must have an active subscription.” Individuals can access courses through LinkedIn Premium, while an organization such as an employer may provide access. LinkedIn’s AI catalog does not establish that its listed courses can be watched free without a subscription, trial, or organizational access.
Some users may qualify for a Premium free trial. Eligibility is limited, trial duration can vary by region or offer, and valid payment information is required. The trial automatically becomes a paid subscription unless you cancel before it ends. Check the terms shown on your account before activating one.
What AI topics can you study on LinkedIn Learning?
The catalog spans introductory AI literacy, applications, ethics and safety, responsible AI, governance, programming, data analysis, machine learning, computer vision, natural language processing, large language models, and prompt engineering. LinkedIn describes the catalog as covering “programming, data analysis, machine learning, computer vision, natural language processing, and more.”
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Examples currently listed in the catalog illustrate its range; their presence does not guarantee free access:
- Introduction to Artificial Intelligence by Doug Rose: 2 hours 26 minutes; released November 21, 2024.
- AI Basics: What Every Professional Needs to Know by Laurence Moroney: 1 hour; released May 11, 2026.
- Artificial Intelligence Foundations: Machine Learning by Kesha Williams: 1 hour 56 minutes; released May 30, 2023.
- Foundations of Responsible AI by Vilas Dhar: 1 hour 8 minutes; released August 25, 2025.
Course offerings change. Treat these as examples, not a definitive list of the newest or best options, and check the live catalog for current availability.
How to choose a course for your goal
Use the catalog’s subject, level, and time-to-complete details to narrow the choices. A course’s length and listing do not establish its teaching quality or guarantee a particular learning outcome.
| Your goal | What to look for | Example direction |
|---|---|---|
| Understand AI at work | Introductory or AI-literacy course; check the level and duration. | “AI Basics: What Every Professional Needs to Know” is a catalog-listed one-hour example. |
| Build technical foundations | Machine learning, Python, data analysis, or related technical subjects. | “Artificial Intelligence Foundations: Machine Learning” is a catalog-listed option. |
| Consider risks and responsibilities | Responsible AI, ethics, safety, or governance. | “Foundations of Responsible AI” is a catalog-listed example. |
To browse and compare, start at the LinkedIn Learning AI course catalog. Confirm the course page’s current details and the access terms visible to your account before enrolling.
A structured option: Getting Started with AI and Machine Learning
LinkedIn Learning lists “Getting Started with AI and Machine Learning” as a seven-course path with ten hours of content. Its stated aims include understanding AI and machine learning, considering accountability and security, analyzing machine-learning models, and developing neural networks with PyTorch and Keras. Listed subjects include AI foundations, linear algebra, deep learning, image processing with Python, reinforcement learning, and hands-on PyTorch.
The path page announces an update for November 2, 2026. If you plan to complete it for a badge, check the live path page for its current course requirements and timing. The page’s one-month trial prompt is not proof that every visitor qualifies for a free trial.
Quick Recap
Check your access before you commit
- Open the course or path page. Review its current title, level, duration, and enrollment details in the AI catalog or the Getting Started with AI and Machine Learning path.
- Check whether you already have organizational access. Your employer or institution may provide LinkedIn Learning. Ask the organization or check the account you use for work or study.
- Review your individual access route. LinkedIn Help identifies an active subscription as necessary for course access and LinkedIn Premium as an individual route. See LinkedIn Learning subscription Overview.
- Read trial terms before starting one. Confirm eligibility, duration, payment requirements, renewal terms, and the cancellation deadline shown to you. LinkedIn says trial details can vary and billing starts automatically after the trial unless you cancel in time; consult its Premium free-trial information.
- Recheck the course’s access status. Do not assume a catalog listing or a course duration means you can watch it without payment. Verify the access option presented on the specific course page while signed in.
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