Passing the AWS Machine Learning Exam

Today, I passed the AWS Speciality exam, AWS Machine Learning (MLS-C01). Unlike other AWS exams, the exam focuses a lot on the various algorithms used in machine learning more than on specific products and what they do.

Why did I write the exam? Since ChatGPT caught the public imagination, there has been much interest in Artificial Intelligence (AI) and Machine Learning. As someone charged with providing sound security advice, I get asked a lot about the right and wrong things with Machine Learning and AI, whether it should be allowed, and what it all means from a security perspective. It is easier to provide such a view if you have a decent handle on the concepts. Of course, there is much to learn and understand, so the learning has just begun.

So what resources did I use to get through it? The best resource for me was the Udemy course: AWS Certified Machine Learning Specialty 2023 - Hands On! course, delivered by Frank Kane. This course contained a lot of good explanations of the various algorithms and how they work in Sagemaker, as well as how to use other products and services. Other helpful course material included the official course book: AWS Certified Machine Learning Study Guide by Shreyas Subramanian and Stefan Natu and the book: AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide by Somonath Nanda. Most important was using AWS products and making them work in practice, loading data, and trying things out. Sagemaker can be expensive, so keep an eye on the billing and remember to shut down services when your stop using them. ChatGPT helped a lot, too, as it could summarise concepts and translate scientific language into plain English. So AI helped me pass the Machine Learning exam. Get a good night's sleep before you write the exam, and do the exam when your brain is engaged.

Good luck.