Exam details

Criteria

The exam tests students in their ability to solve problems by building models using TensorFlow 2.x During the exam, students will complete 5 models - 1 in each of the following categories

  • Category 1: Basic/ Simple model
  • Category 2: Model from learning dataset
  • Category 3: Convolut1onal Neural Network with real-world image dataset
  • Category 4: NLP Text Classification with real-world text dataset
  • Category 5: Sequence Model with real-world numeric dataset

Skills checklist

(1) Build and train neural network models using TensorFlow 2.x (2) Image classification (3) Natural language processing (NLP) (4) Time series. sequences and predictions

Exam environment

  • You can take the exam from any computer that supports the PyCharm IDE requirements, anywhere there is internet, any time. There is no need to go to a test center
  • This exam is an online. performance-based test that requires implementing TensorFlow models using TensorFlow within a PyCharm environment
  • The exam is expected to take up to 5 hours
  • In order to take the exam you will install the TensorFlow Exam plugin using the PyCharm IDE. We recommend you install the PyCharm IDE and become familiar with using it prior to taking the exam. Here are the system requirements for the PyCharm IDE

Candidate identification and authentication

You are required to provide a non-expired Primary ID that contains your photograph. signature and full name (see acceptable forms of ID in the table below)

If your full name on their Primary ID contains non-lat1n characters, then you must ALSO provide a non-expired Secondary ID containing your full name in Latin Characters and signature. OR a notarized English translation of your Primary ID along with the non-latm character Primary ID

Exam time limit

If you do not press the Submit button before the 5 hours has elapsed, your exam will be auto submitted. This in itself does not cause you to fail the exam, but you will only be graded for the questions for which you have already submitted and tested models during the course of taking the exam.

Exam URL

Once you have read this document in rts entirety, you can visit the exam URL here.

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