The exam can be broken down into 4 components: Machine Learning, Azure ML Studio, Azure Products, and Python. Below is a breakdown of the topics I remember from the exam.
These are topics which would be covered in a traditional machine learning course. Here are some of the specific topics I remember.
Evaluation of Linear Regression
Evaluation of Classification
Fisher’s exact test
Deep learning – high-level, what is is for
Neural Networks (RNN vs CNN vs DCN vs GAN)
Azure ML Studio
Azure ML Studio is a major focus of the exam, so you need to be fluent in how to use it. Questions ranged from the basics of how to import data all the way to specifics about certain modules.
missing data questions
There were a number of questions from this category. The question would present you a scenario problem and ask which products would be useful for solving the problem. The questions did not go very deep into any of the products, but you will need to know the purpose of these products.
Azure Machine Learning Service
Blob storage – specifically how to get data in/out
Azure Cognitive Services (high level)
Data Science Virtual Machine
Python was the language of choice for the exam, so focus on it.
Azure Machine Learning SDK for Python
Not on the exam
The following topics were not covered on my exam. The exam questions are pulled from a pool of questions, so it is possible these topics may be cover on a different person’s exam. In any case, these are definitely not major portions of the exam.