Google Cloud launches free AI learning paths

Google Cloud is turning cloud training into something closer to a driving test than a textbook: you do the work in a sandbox, finish the lab, and walk away with a badge that can be shown to recruiters. Its current learning hub, Google Skills, packages that into free paths for artificial intelligence, machine learning, data, and infrastructure instead of leaving people to piece together random tutorials. (cloud.google.com) (skills.google) The company has been moving in this direction for a while, but the platform got a visible reset when Google launched Google Skills as a single home for courses, labs, and credentials. Google said learners completed more than 26 million courses, labs, and credentials in the prior year, which helps explain why it is consolidating everything into one place. (cloud.google.com) A learning path is Google’s version of a guided route through a subject: start with basics, move into product-specific lessons, then finish with a challenge that proves you can use the tools. On the paths page, Google groups these routes by role and topic, including cloud engineering, data work, and generative artificial intelligence. (skills.google) The practical hook is the lab. Google says its hands-on labs run in a sandbox environment, which means learners can use real Google Cloud tools without setting up their own company account or risking a production system. (cloud.google.com) The badge is the credential layer on top of that lab work. Google describes skill badges as digital credentials earned by completing hands-on courses or challenge labs, and says they are meant to be shared on resumes and social profiles as proof of product-specific ability. (cloud.google.com) (skills.google) A lot of the new attention is around Gemini, Google’s family of artificial intelligence models and assistants. Google now has paths where Gemini is not just the topic of a lecture but part of the workflow, including courses on building applications with Gemini and Streamlit, a Python web app framework, then deploying them on Cloud Run, Google’s managed app service. (skills.google 1) (skills.google 2) Another track pushes beyond demos into operations. Google’s Production-Ready AI path, launched in November 2025, covers security, infrastructure, monitoring, Vertex AI, Google Kubernetes Engine, and Cloud Run, which is the difference between “I made a model answer a prompt” and “I can keep an AI service running for users.” (cloud.google.com) There is also a split between beginner and advanced material that makes the catalog wider than a single “learn artificial intelligence” course. Google lists beginner introductions to generative artificial intelligence alongside intermediate and advanced paths for artificial intelligence infrastructure using graphics processing units, tensor processing units, and Google Kubernetes Engine. (skills.google 1) (skills.google 2) That changes the value of a side project. A personal system-design repo or infrastructure demo still shows initiative, but an official lab badge adds a second signal: Google is saying you completed a specific task set inside its own tools. (cloud.google.com 1) (cloud.google.com 2) The bigger play is not hard to see. Companies want workers who can use artificial intelligence tools now, and Google wants those workers learning on Google Cloud first, inside Google’s labs, with Google’s badges, and eventually on Google’s paid services and certifications. (cloud.google.com) (cloud.google.com)