In the course Artificial Intelligence for Trading on Udacity, you will learn the basics of quantitative trading, including market mechanics and how to generate signals with stock data. You will also develop a momentum-trading strategy in your first project. As you progress, you will learn advanced quantitative methods commonly used in trading, such as breakout strategies. Additionally, you will explore portfolio optimization and financial securities formed by stocks, including market indices, vanilla ETFs, and Smart Beta ETFs. The course also covers alpha and risk factors, and teaches you how to construct a portfolio using advanced optimization techniques. You will also learn about sentiment analysis with natural language processing, including analyzing corporate filings to generate sentiment-based trading signals. The course delves into advanced natural language processing with deep learning, where you will learn to apply deep learning in quantitative analysis using recurrent neural networks and long short-term memory to generate trading signals. You will also learn techniques to select and combine factors generated from both traditional and alternative data. Finally, the course teaches you how to refine trading signals by running rigorous back tests and track your profit and loss while your algorithm buys and sells.