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The TensorFlow Developer Certificate exam assesses your ability to solve problems by building models using TensorFlow 2.x. Here’s what you need to know:

1. Exam Details:
   • The exam tests your skills in developing software programs using TensorFlow.
   • You’ll demonstrate your understanding of TensorFlow APIs, debugging, and model creation.
   • The exam focuses on building and training neural network models using TensorFlow 2.x.
   • You’ll work with machine learning (ML) models, preprocess data, and predict results.
   • Strategies to prevent overfitting, batch loading of data, and using callbacks are also covered.
   • The exam duration is up to 5 hours.
2. Skills Checklist:
   • TensorFlow Developer Skills:
     • Proficiency in Python programming, resolving Python issues, and running Python programs.
     • Finding information about TensorFlow APIs (guides, references, etc.).
     • Debugging and solving errors from the TensorFlow API.
     • Creating ML models with reasonable model sizes.
     • Understanding compatibility differences between TensorFlow versions.
   • Building and Training Neural Network Models:
     • Using TensorFlow 2.x.
     • Compiling and training ML models.
     • Preprocessing data for model use.
     • Building sequential models with multiple layers.
     • Handling binary classification and multi-class categorization.
     • Plotting loss and accuracy.
     • Preventing overfitting (augmentation, dropout).
     • Using pretrained models (transfer learning).
     • Ensuring correct input and output shapes.
     • Working with datasets in different formats (JSON, CSV).

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