What is learning path for being good in Machine Learning

Hi @LarengeKamal,

one of our mentors @saifkhanengr published an excellent outline on how a possible course sequence can look like: check out this post!

A quite classic sequence which I observed more and more among fellow learners is:

  • AI for everyone (if you are a beginner) [I understand this is where you currently are - pls. correct me if this is not correct]
  • machine learning specialization for the basics and core concepts
  • 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)

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 this thread: Please help with course selection - #2 by Christian_Simonis

Best regards
Christian

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