This lecture provides a general introduction into learning by rewards, focusing on examples from deep reinforcement learning presented without mathematical details. Topics covered include action learning, learning from mistakes and successes, deep reinforcement learning in games like chess, and the use of artificial neural networks for reward-based learning.