Course Overview

The course is primarily based on the fundamentals of reinforcement learning (RL). With the help of this course, students will gain the knowledge and skills to utilize RL and apply it for valuation training and asset management.

These skills will help solve financial problems, such as algorithmic trading, risk management, and portfolio optimization. Students will be able to practice the examples using Q learning. Moreover, they can apply knowledge that will be acquired in the course to measure market dynamics. All in all, the course will help in understanding the ways of finance and its management through RL.

What you'll learn

• Q-Learning: You will understand how to use Q-learning to solve problems in the finance industry.
• Option Pricing: You will learn how to apply RL techniques so that the pricing models improve and there is better risk management.
• Models of Market Dynamics: You will create models that predict the market and tell you about market behavior and volatility.
• Optimal Trading: You will learn how to make trading strategies that can change according to the market conditions.
• Risk Management: You’ll learn some RL techniques that help in assessing risk and managing portfolios.

Requirements

• Basic knowledge of data management.
• A computer or laptop with internet connectivity.
• A flexible work schedule to dedicate to your studies.

Advantages of Reinforcement Learning in Finance Course

Enroll Free

Growth in Career:

This certificate can help you make a career in Finance as an RL specialist. Finance is a high-paying field, and RL specialists can get even higher salaries compared to traditional analysts.

Industry Value:

This course is developed by the State University of New York, so it has high value in the industry and is a good way to certify your skills.

Portfolio Building:

As you will get practical knowledge and projects, you can easily create a portfolio from them and apply for jobs after the course.

Increased Professional Network:

You can have direct contact with industry professionals, data scientists, and other students with whom you can learn and grow together.

Skills For Future:

Financial markets are now becoming automated, so it’s good to have expertise in relevant skills like Reinforcement Learning.