The course is designed to not be too tool-focused or dependent on any specific tool such as Azure, R, Python, etc. The idea is to go through the process, step by step, so you understand the concepts and critical thinking behind data science and machine learning – the whole process from knowing how to identify your business problem, to understanding your dataset and the right machine learning algorithm to solve the problem, to choosing the right metric to evaluate your model, etc.
The reason we use Azure Machine Learning is because it’s an easy interface to work with, especially for those who have no programming or coding background. To not get bogged down into programming and miss important concepts of machine learning, Azure can help lower the barrier for people wanting to ramp up quickly. We also teach students the R commands when implementing models, and these are fairly easy to implement compared to using a fully-fledged programming language. R is core to data science, it is very wide spread and used throughout industry to build machine learning models. You may also use Python, another commonly used language. Azure allows you to execute your R scripts, so you do not have to only interact with Azure’s interface once you complete the course.
We have a bunch of online videos that can help you get started in using Python and R for different basic data science tasks: https://tutorials.datasciencedojo.com/ This Getting Started with Python and R for Data Science might be useful to watch, to give you an idea: https://tutorials.datasciencedojo.com/getting-started-with-python-and-r-for-data-science/
Taking the in-person course will give you a much more detailed run-down of every step that is needed to properly tackle common data science problems and work with different datasets to cover a range of problems to solve using data science.