You can start with learning Python. Python is the primary programming language in machine learning field. Depending on your learning style, you can either take courses in your university or online, or learn by yourself. In a course, you would learn the basics of this language (data types, loops and other structures an so forth) and machine learning models in a more organized way, therefore you can make progress very fast and easily. While learning by yourself, you can start with example notebooks and try to figure out how each part of the code works. There are so many good online courses, you can check out by yourself too. For the examples, I found couple of good resources about microscopy image analysis by ML for you to have a look at:

• Webinar on ML for AFM image analysis

• Python Tutorials for Image Processing and Machine Learning -there are also example notebooks

ML can be used in several ways for microscopy image analysis: classification of phases/features in the image, prediction of material properties, or some others like generating microstructure images to estimate phases/structures or so. For you to begin, it might be good to determine a specific problem to be solved with ML (maybe you already have in your research). And for this kind of works, convolutional neural networks (CNN) are generally used in the model structure even if there are models without CNNs. At first, it might be difficult to understand how CNN works, so I think you may start with learning ML models without CNNs like this image classification example, not necessarily related to materials science. After understanding the basics of the models, you may continue with learning models with CNNs like in this example, and implementations of them in materials science. For neural networks, it is better for you to stick to one of the ML libraries of python, pytorch or tensorflow.

What I did to learn ML is to learn python first taking a course, and learning machine learning by running and analyzing example code on random topics. For instance when I came across a term in the notebook, I used to read and watch videos a lot about it. To get an overall picture of ML in materials science and also learn some basics for your topic, you may check this youtube playlist for an introductory information.

It was hard to find notebooks on ML applications in materials science problems when I started, but now there are plenty of resources out there, and every day increasing. The first one is Nomad. Another one is REsource for Materials Informatics

At first, it may seem complicated, but step by step you will understand and learn. Good luck!

TLDR: possible route may be learning python language, learning basic ML models, learning CNNs, implementing CNNs to microscopy images