 Cervical spinal cord injuries frequently cause paralysis of all four limbs, a medical condition known as tetraplegia. Functional electrical stimulation, FES, when combined with an appropriate controller, can be used to restore motor function by electrically stimulating the neuromuscular system. Previous works have demonstrated that reinforcement learning can be used to successfully train FES controllers. Here, we demonstrate that transfer learning and curriculum learning can be used to improve the learning rates, accuracies, and workspaces of FES controllers that are trained using reinforcement learning. This article was authored by Douglas C. Crowder, Jessica Abru, and Robert F. Kirsch.