Going beyond Keras - customizing with TensorFlow

Data Scientist

If you've completed the first module and realized that you need extra flexibility to build or debug your model, then this module is for you. We'll show how you can create a simple neural network for image classification, but this time we'll use lower-level TensorFlow code and explain the foundational concepts needed to understand it.

Learning objectives

In this module you will:

  • Learn basic TensorFlow topics, such as tensors, variables and automatic differentiation.
  • Learn the difference between eager and graph execution.
  • Re-implement the train, test, and prediction phases of an existing Keras project using TensorFlow.


  • Basic Python knowledge.
  • Basic knowledge about how to use Jupyter Notebooks.
  • Completion of module 1 of this learning path or knowledge of Keras.