This TensorFlow 2.0 complete course is designed to introduce beginners to deep learning and neural networks using Python. It focuses on practical implementation while building a strong understanding of core machine learning concepts.

The course starts with an introduction to TensorFlow 2.0 and how it simplifies building deep learning models compared to earlier versions. You will learn how to set up your environment and begin working with tensors, the fundamental data structure used in TensorFlow.

A major part of the course is dedicated to building neural networks from scratch using the Keras API. You will learn how to design models, train them on datasets, evaluate performance, and make predictions. The course explains key concepts such as loss functions, optimization, and model accuracy in a simple and clear way.

You will also explore practical applications, including image classification and basic computer vision tasks. These examples help you understand how neural networks are used in real-world AI systems.

The course emphasizes hands-on learning, making it ideal for beginners who want to start building AI models quickly. By the end of this course, you w