Keras Deep Learning Online Course
This comprehensive course starts by laying a strong foundation in Python, covering essential programming concepts like variables, control structures, lists, tuples, dictionaries, and functions. It then introduces the powerful NumPy library for efficient handling of large arrays and matrices. To build a solid understanding, the course delves into the theory behind deep learning—explaining the structure of artificial neurons and how they form complex neural networks.
As you progress, you’ll explore advanced deep learning topics such as convolutional neural networks (CNNs), text-based models, binary and multi-class classification, and image processing. The course culminates with an in-depth focus on Generative Adversarial Networks (GANs), guiding you from the fundamentals to practical applications.
Who Should Take this Course?
This course is ideal for beginners who aspire to gain expertise in deep learning and GANs. Whether you're aiming to become a machine learning engineer, deep learning specialist, AI researcher, data scientist, or GAN developer, this course will help you grow from foundational skills to advanced knowledge through immersive, hands-on learning.
What You’ll Learn
- The fundamentals of Artificial Intelligence (AI) and machine learning
- Deep learning concepts and neural network architectures
- Python programming essentials: lists, tuples, dictionaries, and functions
- Core libraries: NumPy, Pandas, and Matplotlib
- Structure and function of artificial neurons and neural networks
- CNN components including stride, padding, and flattening
- Advanced topics including image classification and GANs