Machine Learning In Algorithmic Trading (Udemy.com)

I'm a final year, university undergraduate Computer Science student and this course so far has been exactly what I was looking for ! It expands on topics that I've encountered during my studies, with direct and relevant implementation.

Very interesting and insightful course that provides solid foundation for applied machine learning in trading, from where one can take it in many different directions. Dr Ziad is amazing in breaking down complex concepts into digestible chunks. I participatory enjoyed that the course is spending significant amount of time on data/feature engineering and not just using algorithms on pre-made datasets.

This course was a great introduction to trading algorithms, it gave me clarity on how to organize the codes and how to THINK about the entire structure of the algorithm, it certainly added a lot of knowledge.

I used this course as an introduction to ML and found it very insightful. It does cover a lot of concepts and, as such, it was sometimes difficult to understand how it all fits together. I appreciate that there is no single solution with ML, so that is understandable.

I mostly listened to the course as an audiobook, and Dr. Ziad Francis’s soothing voice really helped me focus on what he was seeing—a strange but effective phenomenon when your instructor is calm, clear, and never in a hurry to impress. Unlike many other overconfident courses where the instructor oversells and underdelivers, Ziad’s course is the opposite. Understated, methodical, and refreshingly grounded in reality. He starts with a basic but solid primer on machine learning fundamentals, gently weaving in evaluation metrics and feature engineering in a way that’s digestible even without a screen in front of you. Then, he transitions into one of the most important but overlooked aspects of quant modeling—data leakage. Not just a throwaway mention, but a careful walkthrough that demonstrates how easily leakage can creep in, and how devastating its impact can be when left unchecked. The course builds patiently toward a simple trading strategy, and Ziad never pretends it will make you rich. Instead, he shows how this bare-bones strategy forms a scaffold you can gradually enhance with the right applications of machine learning. The result is an honest, instructive arc from theory to application, without any flashy clickbait promises or convoluted code dumps. I will now listen to his Algorithmic Trading course on my walk, fully expecting the same quiet competence and clarity. And I sincerely hope he creates part 2 and part 3 of this series—more detailed explorations of machine learning in trading. Without, of course, giving his secret edge away.

Loved it, great intro to ML. I would have preferred it to have a little more focus on trading/backtesting aspect, but the instructor provides a good foundation for you to go off and do your own thing. Highly recommend!

Overall, it is a good course. I definitely learned something. I would love to see some practical tasks, where we would do a homework on our own first and then compare it with the solution. Also, a big portion of the course was dedicated to introduction into ML models. There isn't much trading specific knowledge there and it might be not as useful for people who already have ML experience.

Lots of introductory information that I was not aware of when it comes to machine learning. It explains the importance of labeling data however and the limitations of models. Do not expect to walk out of this course with a bot that you can test or tweak. Would have like to see a section that showed how a model can be exported and enhanced. As well as a section on using live data or simulated live data using new candles through an API or CSV. Technical analysis traders looking to have machine learning do their whole trading will need to look deeper into more code related courses that will teach them how to get entry signals for their strategy and then look into this course to enhance and code a model that signals if the entry is good or not.

This is a great course as a starting point for understanding how we can leverage ML for trading. The explanations are good and there are plenty of practical Python examples. I would have liked to have some more Python examples of how to use ML in different ways than using it to directly predict market inputs and outputs. For example, the course mentions several times that we can start with a classic algorithmic strategy and use ML to refine it and make it more profitable based on the good or bad inputs of this system. It would have been great to see this in practice with Python. In any case, thank you very much for this course, I have enjoyed it and learned a lot of useful things.

It is an excellent course for Machine Learning. It covers the theoretical parts of machine learning and AI and python is used to demonstrate the application of the theoretical models on real time trading data. The next step is to follow Dr Ziad on his youtube channel where up to date information is provided on a weekly basis.