# AI credits for teaching URL: https://research-memex.org/docs/implementation/ai-environment-setup/course-ai-funding Description: Find support for students building with AI: coding assistants, cloud credits and managed project labs. *Support for what your students want to build.* Some education offers help students write software. Others pay for the models and cloud services that software uses. For a class building AI applications, you may want both: a coding agent to develop the application, and cloud credits to run it. ## Build applications with a coding agent [#build-applications-with-a-coding-agent] GitHub Copilot is a useful starting point for a course where students build a website, prototype an application or learn to work with coding agents. Copilot can help implement features, fix bugs and write tests. Its [agent tools](https://docs.github.com/en/copilot/concepts/agents/cloud-agent/about-cloud-agent) go beyond suggesting the next line of code. Verified teachers and students can get free Copilot benefits through GitHub Education. Follow the separate [teacher](https://docs.github.com/en/copilot/how-tos/copilot-on-github/set-up-copilot/enable-copilot/set-up-for-teachers-and-os-maintainers) and [student](https://docs.github.com/en/copilot/how-tos/copilot-on-github/set-up-copilot/enable-copilot/set-up-for-students) routes for the included features and usage allowances. This supports the work of building an application. It does not pay for external model APIs or hosting that the finished application uses. ## Run a class project on Google Cloud [#run-a-class-project-on-google-cloud] Google Cloud teaching credits suit a course where students experiment with model APIs, build AI workflows or host applications with storage and other cloud services. Google's teaching-credit route starts with a faculty application. The [application](https://edu.google.com/programs/credits/teaching/?modal_active=none) asks what the course will do with Google Cloud and how many students will participate. See the [eligibility rules](https://support.google.com/google-cloud-higher-ed/answer/10723190?hl=en) for supported institutions and countries. The award's eligible services matter more than the provider's model catalog; check coverage for the models your project needs. Have an award already? [Redeem it](#redeem-your-award). With an assigned Cloud project, go straight to [Vertex AI setup](/docs/implementation/ai-environment-setup/vertex-ai-setup#check-your-project), then connect a desktop client or your own application. ## Give students room to experiment on Azure [#give-students-room-to-experiment-on-azure] [Azure for Students](https://azure.microsoft.com/en-us/free/students/) is an individual route: eligible students sign up for their own credits, with no credit card required. It is worth exploring for independent projects and capstones that combine AI, data and a hosted application, especially when students want to choose what to build rather than follow a shared lab. The offer excludes third-party and Marketplace products. The [offer terms](https://azure.microsoft.com/en-us/pricing/offers/ms-azr-0170p/) explain eligibility and coverage; a model being available somewhere in Azure does not mean this student offer funds it. ## Teach cloud deployment in managed labs [#teach-cloud-deployment-in-managed-labs] [AWS Academy Learner Lab](https://aws.amazon.com/training/awsacademy/) provides managed environments for your own assignments, with selected AWS services and usage monitoring. Educators use it through an [AWS Academy member institution](https://aws.amazon.com/training/awsacademy/faq/). This is most relevant when cloud infrastructure is part of the learning: deploying an application, connecting services or building a data pipeline. For a class that only needs access to a chat model, it is a less direct fit. Check the lab's available services before designing an AI assignment around it; this is not an unrestricted model-API allowance. ## Redeem your award [#redeem-your-award] For Google teaching credits, Google sends staff coupons and a separate student verification link. Follow the [award instructions](https://docs.cloud.google.com/billing/docs/how-to/edu-grants) and check your award's redemption deadline and expiry. Google says education-credit redemption does not require a credit card. A card prompt is a reason to check the [coupon route](https://support.google.com/google-cloud-higher-ed/answer/10322773?hl=en). After redemption, [check your Cloud project](/docs/implementation/ai-environment-setup/vertex-ai-setup#check-your-project). If your course instead supplies an API key, use the [API-key guide](/docs/implementation/ai-environment-setup/api-keys-setup-guide) and [Cherry Studio](/docs/implementation/agentic-ai-tools/cherry-studio-setup-guide).