One possibility is GPU acceleration using the cuML framework, but if you are must use a specific framework like sklearn it won't be feasible. https://medium.com/rapids-ai/accelerating-random-forests-up-to-45x-using-cuml-dfb782a31bea

There are some alternatives such as Google, AWS, Gradient, you may be able to get student credits. Also, even if you don't need a GPU, you can rent an instances with many CPU cores at Vast.ai for cheap (even with the GPU it's cheaper than a CPU only AWS instance with the same amount of cores), for example the cheapest instance with 16vCPU is < $0.20/hour and only needs a credit card. The main issue with vast.ai is that you should save your results before shutting down the instance because they are tied to the machine which may become unavailable.