Deep Q Learning **WITHOUT** OpenAI Gym
You can take a code of an environnement such as a game and then you implement your algorithms. 
But think to be explicit in your code for the rewards and the actions. Return a reward for each action. 
If you want to start RL without Gym. Try to do a simple game and implement NEAT algorithm. And then try to implement Q-learning and modify your code to add a reward for each action.
Does anyone have or know of any tutorials / courses that teach q learning without the use of open ai gym.
I'm trying to make a convolutional q learning model and I have no problem doing this with pytorch and open ai gym, easy! but when I try and apply it all to an environment that isn't in open ai gym its a whole different story, trying to apply this to other games that aren't Atari so I don't have access to the env.reset and all those other nice options, it becomes a whole new ball game. If someone knows of a place to learn this or who is willing to teach me / help me with it I am more than willing to pay for any help as well.
Thanks.