# How to Learn AI [How to Learn AI](https://pub.towardsai.net/how-to-learn-ai-1b9814ed3681) [How to Learn Python for Machine Learning](https://machinelearningmastery.com/how-to-learn-python-for-machine-learning/) [Do you need a Master’s Degree in Data Science?](https://towardsdatascience.com/do-you-need-a-masters-degree-in-data-science-you-are-asking-the-wrong-question-8c83dec8bf1b?source=rss----7f60cf5620c9---4) **NOTE:** The Medium and TowardsDataSciene articles can be viewed in a browser Private tab if you do not have a subscription. ## Tutorials and Books Choosing an ML learning resource is primarliy a matter of personal preference. In geneal, I recommend that you refer to more than one resource (other than scikit-learn, tensorflow, and PyTorch documentation) when learning ML. [AI Learning Resources](https://aicoder.medium.com/ai-learning-resources-b49da21fd3b8) ## Consulting and Freelance If you ever do paid consulting or freelance work in the U.S., you should be aware that there are legal implications and I found [TODO] to be a clear, concise resource on the topic. I am sure there are similar rules and regulations in the EU and elsewhere. ## References [1]: [Applied Machine Learning Process](https://machinelearningmastery.com/start-here/#process) [2]: [Understand Machine Learning Algorithms](https://machinelearningmastery.com/start-here/#algorithms) [3]: [Stop Coding Machine Learning Algorithms From Scratch](https://machinelearningmastery.com/dont-implement-machine-learning-algorithms/) [4]: [5 Mistakes Programmers Make when Starting in Machine Learning](https://machinelearningmastery.com/mistakes-programmers-make-when-starting-in-machine-learning/) [5]: P. Bourque and R. E. Fairley, Guide to the Software Engineering Body of Knowledge, v. 3, IEEE, 2014.