It's important to have basic-intermediate Python knowledge with a specific focus on NumPy.All the examples are based on Python 3.5+. It is suggested to use the Anaconda distribution (https://www.anaconda.com/download/ ), which is probably the most complete and powerful one for scientific projects. A good mathematics background is necessary to fully understand the theoretical part. In particular, basic skills in probability theory, calculus, and linear algebra are required.
To practice the TensorFlow chapter, you will need Docker and Kubernetes installed. It's preferable that the reader has GPU hardware but it's not necessary.