Here you can find material that you can use to prepare yourself, or simply to expland your knowledge in different areas.
TF1.X (more focused on Theory)-Applied Deep Learning - A Case-Based Approach to Understanding Deep Neural Networks, Umberto Michelucci, APRESS 2018 (available as PDF or printed version)
https://www.apress.com/gp/book/9781484237892
TF1.X/2.X - Advanced Applied Deep Learning - Convolutional Neural Networks and Object Detection, Umberto Michelucci, APRESS 2019
https://www.apress.com/gp/book/9781484249758
TF2.X - Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, 2nd Edition, Aurélien Géron, O'Reilly 2019
TF2.0 - Hands-On Neural Networks with TensorFlow 2.0, by Paolo Galeone
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TF1.X - Learn Keras for Deep Neural Networks - A Fast-Track Approach to Modern Deep Learning with Python, Moolayil, Jojo John, APRESS 2018
https://www.apress.com/gp/book/9781484242391
A very good book that you can access completely in Google Colab is the "Python Data Science Handbook". This can be found here