Getting Started with TensorFlow (2026)

Building and training deep learning models can be complex, especially when dealing with model architecture design, training stability, and performance optimization across different hardware environments.
In this course, Getting Started with TensorFlow, you'll gain the ability to build, train, evaluate, and customize neural network models using TensorFlow and Keras.
First, you'll explore TensorFlow fundamentals, including tensor operations, execution modes, and environment setup with hardware acceleration.
Next, you'll discover how to design and train neural networks for regression and classification, along with techniques for optimization, regularization, and evaluation.
Finally, you'll learn how to customize models using the Functional API, implement advanced architectures such as multi-input and multi-output networks, and extend TensorFlow with custom layers and callbacks.
When you're finished with this course, you'll have the skills and knowledge of TensorFlow needed to confidently develop and optimize end-to-end deep learning solutions.
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