Please help with course selection

I am enrolled in the Machine Learning Course and will finish it this week. I am a little confused about if taking the Deep Learning specialization is the way to go ahead or have the same topics already been covered in the Machine Learning course. Thanks in advance!

Hi @Samarth_Minocha

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:

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

Thank you so much for your response! I think I should take the Tensorflow course after the ML specialization so that I can get more comfortable with the practical execution and thereafter go for the DeepLearning course. I have a doubt though are the concepts covered in ML specialization enough for the TensorFlow course?

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Hi @Samarth_Minocha, from my personal experience, I think taking Deep Learning Specialization is the way to go, since in TensorFlow Dev. Sp. some concepts covered in Deep Learning Sp. will be necessary. Of course, this is not mandatory.

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Ok, thank you so much!

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Hello Samarth,

Adding to Nydias’ suggestions.

As I myself did first DLS course specialisation and during the second course of DLS where Andrew mentions to do TensorFlow course, thereby I continued doing both. If you are planning for any AI app model algorithm then surely doing DLS should be first choice but then what I felt personally when I did TensorFlow, I could understand some of the concept of DLS more properly, So after finishing the first course of DLS, simultaneously please do TensorFlow course as both course help one understand some concepts in the other specialisation. I would only suggest you to do this way if you have a dedicated time as it requires patience, concentration and time to understand what Andrew and Lawerence are both teaching are part of a whole model training.

Having completed all these specialisation

I would prefer doing this way

  1. DLS specialisation
  2. Machine learning specialisation
  3. Tensorflow Developer ( start doing after complete course 1 of DLS specialisation)
  4. TensorFlow Data based
  5. TensorFlow Advanced Technique