My take: the best personal sequence for you depends on:
- where you stand now (e.g beginner or medium)
- what you want to achieve (e.g. become an AI engineer in the field of IoT / Automotive)
- your strength and background of the industry you want to work (e.g. background in image processing with focus on sensor fusion and deep learning)
- your timeline, considering how much time you want to invest in your learning roadmap (e.g. 5 hours per week for 8 months or so)
see also these threads:
- How to become an AI Engineer - #4 by Christian_Simonis
- After completing DLS, what’s next - #4 by Christian_Simonis
A quite classic sequence which seems to be popular among fellow learners seems to be:
- AI for everyone (if you are a beginner)
- machine learning specialization for the basics and core concepts [I understand this is where you currently are]
- deep learning specialization if this suits your plans and you work rather with big unstructured data and want to apply or work with CV, NLP, LLM etc.
- (MLOps, LLM specialization or TF specialization dependent on your requirements and plans)
So, I would suggest to check out the deep learning specialization page and check if the outlined scope matches your expectations and plans!
Best regards
Christian