Thread by @RisingSayak

Got the @TensorFlow Developer Certification.

Thanks to the #ML @GoogleDevExpert program for sponsoring the exam.

In this thread, I will summarize my experience.

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If you use @TensorFlow in your work moderately, I think you already have the prerequisites. Definitely take the *TensorFlow in Practice* specialization by @lmoroney & @DeepLearningAI_. It will get you up to speed.

Study the contents rigorously.

Review the certificate handbook carefully. It really has all the information you need to know about the certification - tensorflow.org/extras/cert/TF….

* Install @pycharm & get sufficiently comfortable with it.
* Set up the exam environment properly.

There will be an additional exam guide (confidential, isn't meant to be shared) made available to you. I found it particularly very useful while giving the exam.

If a test-case fails don't panic. Go through the corresponding section in the guide, study it, and come back.

I ran all of my code on @GoogleColab because my local machine is a very humble one. I downloaded the saved models and copied them over to the respective exam directories and then submitted them for evaluation.

I found the notebooks shown by @lmoroney in the TensorFlow in Practice specialization to be really good reference points during the exam.

The exam allows referring to online resources which is pretty cool. I had fun giving the exam which is definitely important.