Welcome buddy, I am more than happy to share my learning guide. Initially, It was really difficult on where to start and which course to take. Most of the courses seem to get in to the topic very fast or not clearly explaining. In fact most of the courses were like just reading from a book with no proper detailing of the concept. After multiple stumbling I found this book https://web.stanford.edu/\~jurafsky/slp3/ . This book is up to date with clear explanations. Although it is clear, I have to search on the internet to understand better and learn more to complete the exercises mentioned in the book. This book was really helpful in understanding concepts and technical terms used in nlp.
After reading that book I wanted to get started with actual hands on. So I started this one https://www.coursera.org/learn/natural-language-processing-tensorflow/home/welcome. But on first video of Week 2, I realized that without Neural networks knowledge, it is not possible to go further. Then like everyone I enrolled in Andrew Ng's https://www.coursera.org/learn/machine-learning/home/welcome. After both the courses I started these 4 courses https://www.coursera.org/learn/classification-vector-spaces-in-nlp?specialization=natural-language-processing. I am currently on course 2/4. These courses have lots of assignments and optional excersises which helped me to write actual code for nlp.
As of then, I have learned to use nltk and TensorFlow but there are other powerful libraries like Spacy and PyTorch are available. So I started to redo the exercises with those libraries. We cannot expertise all the libraries so trying to learn as much as I can in these. One more thing I learned is choosing correct training dataset is more important for the project.
I have started my journey at May, 2021. With in these six months I had come up to only this far. There are more things to explore. Sometimes I want to read published papers on nlp and machine learning. But I cannot understand most of it, too much maths. I guess still a long way to go.