Reinforcement Learning for ML/AI

Reinforcement Learning(RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences.

Though both supervised and reinforcement learning use mapping between input and output, unlike supervised learning where feedback provided to the agent is the correct set of actions for performing a task, reinforcement learning uses rewards and punishment as signals for positive and negative behaviour.

In this course, Reinforcement Learning in Machine Learning you will be introduced to Reinforcement Learning, an area of Machine Learning. You will learn the Markov Decision Processes, Bandit Algorithms, Dynamic Programming, and Temporal Difference (TD) methods. You will be introduced to Value function, Bellman Equation, and Value iteration. You will also learn Policy Gradient methods. You will learn to make decisions in an uncertain environment.

Since Irizpro offers live-instructor-led training, you get the benefit of direct and on-spot access of a virtual classroom, unlike a recorded version where you may have to depend on external sources for clearing your doubts.

Browse on more for detailed course curriculum, assessment pattern and certification.

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About Irizpro Courses: All our courses are Live, Virtual Classroom-based sessions. So, the instructor is live sharing the screen with the participants. The sessions are open to questions and discussions. Post the course completion, the recording of the same is shared with the participants for future reference. The maximum number of participants allowed in each batch is 15 only so that a quality interaction can happen between the instructors and participants. All courses are certified by IRIZPRO Learning Solutions.

How to Enroll for this course at Irizpro?

You can buy this course from this section and we will reach out to you with all the relevant enrolment and batch starting date on your email.

Alternatively, if you wish to consult with us before enrolling, or other admission schemes we may be offering, feel free to write to us at [email protected] or call/whatsapp at 7506937544