Algorithmic Trading – Machine Learning & Quant Strategies Course with Python

in this comprehensive course on algorithmic trading you will learn about three cuttingedge trading strategies to enhance your financial toolkit latchezar teaches this course he is an experienced quantitative researcher and data scientist in the first module you'll you'll explore the unsupervised learning trading strategy utilizing SP 500 stocks data to master features indicators and portfolio optimization next you'll leverage the power of social media with the Twitter sentiment investing strategy ranking NASDAQ stocks based on engagement and evaluating performance against the QQQ return lastly the intraday strategy will introduce you to the gar model combining it with technical indicators to capture both daily and intraday signals for potential lucrative positions hello and welcome to this free code Camp course on algorithmic trading machine learning and Quant strategy with python my name is we are going to develop three big quantitative projects from start to end and the course overview would be the following first we're going to talk about algorithmic trading Basics then we're going to talk about machine learning in trading some obstacles and challenges we may face while using machine learning in trading then we are going to develop the first project which would be an unsup rised learning trading strategy using stocks from S&P 500 the next project would be Twitter sentiment and it would be using data from NASDAQ 100 stocks and the third one would be focusing on one asset it would be an intraday strategy using a gar model to predict the volatility it would use simulated data and after that we are going to have a quick wrap up and with that we'll finish the tutorial but before we continue I would like to mention that this tutorial