AI Engineer

Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by interacting with an environment. Unlike traditional supervised learning, RL does not rely on labeled data. Instead, the agent learns by taking actions and receiving feedback in the form of rewards or penalties. Over time, it aims to maximize cumulative rewards by refining its strategy based on past experiences. RL is often used in areas like robotics, game AI, and autonomous systems, where the goal is to develop intelligent behaviors through trial and error.

While a degree in computer science, data science, or a related field can provide a solid foundation for becoming an AI engineer, it is not strictly necessary. Many successful AI engineers are self-taught or have gained expertise through online courses, certifications, and hands-on projects.