Updated in May 2025.
This course now features Coursera Coach!
A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.
This comprehensive deep learning course offers a practical journey from the basics to advanced concepts. It starts with perceptrons and neural networks, progressing through key topics such as backpropagation, convolutional neural networks (CNNs), and transfer learning.
You'll gain hands-on experience with tools like TensorFlow and Keras, applying deep learning techniques to real-world applications such as medical image analysis and natural image classification. The course ensures you learn not only the theory but also how to build, train, optimize, and deploy neural networks.
By the end, you'll have a robust portfolio of projects, showcasing your deep learning skills. Perfect for data scientists and ML engineers, this course requires a basic understanding of Python, mathematics, and ML algorithms. Whether you're advancing your AI career or starting your journey in data science, this course equips you with essential knowledge and practical expertise in deep learning.
Applied Learning Project
The included projects are designed to solve authentic problems by applying deep learning techniques to real-world datasets. Learners will engage with practical applications such as analyzing natural images, diagnosing medical conditions using X-ray images, and implementing advanced recurrent neural network models for tasks like text generation and part-of-speech tagging. These projects ensure that learners not only understand theoretical concepts but also gain hands-on experience, enabling them to apply their deep learning skills effectively in real-life scenarios.
