This comprehensive TensorFlow course is designed for beginners who want to learn deep learning, neural networks, and artificial intelligence using TensorFlow. The course starts with the fundamentals of AI, Machine Learning, and Deep Learning, helping learners understand the differences between these technologies and their real-world applications.
You will learn how neural networks work, including the core concepts behind artificial neurons, layers, activation functions, and model training. The course then introduces TensorFlow, one of the most widely used deep learning frameworks for building and deploying machine learning models.
The training covers TensorFlow installation, environment setup, and hands-on development with TensorFlow 2.0. You will explore how to create, train, and evaluate neural network models while understanding the underlying deep learning workflow.
A dedicated section focuses on Artificial Neural Networks (ANNs), teaching how machine learning models learn patterns from data. The course also introduces Convolutional Neural Networks (CNNs), a powerful architecture used for image classification, computer vision, and object recognition tasks.
Throughout the course, practical demonstrations and explanations help reinforce key concepts, making it suitable for students, developers, and aspiring AI engineers. By the end, learners will have a solid understanding of TensorFlow, neural networks, and modern deep learning techniques used in real-world AI applications.
