I am not sure if this is a right place to ask this question, but I appreciate any insights.
I am finishing up the course 2 today, and I was wondering if this is enough to jump onto course 5. I am interested in NLP application and my practical goals are to train NLP models through python packages such as spaCy and AllenNLP. My learning goals from this course are:
- gain enough understanding to select appropriate neural net architecture for NLP tasks at hand.
- learn enough basics to read some prior research (conference papers in NLP).
- learn to implement transformer architecture, and
- learn to implement fine tuning through existing packages such as spaCy and AllenNLP.
I think the course 1 and 2 covered enough basics of Deep Learning, and I wonder if I can jump right onto Course 5, which align more with my learning goals listed above. I appreciate any suggestions on this!