Deep Learning
Course Overview
About The Course
The “Deep Learning” course at Sonek Data School offers an in-depth exploration of neural networks and advanced AI techniques. Students will learn to build, train, and optimize deep learning models, covering key topics such as convolutional and recurrent neural networks, transfer learning, GANs, and reinforcement learning. With a strong emphasis on practical applications and hands-on projects, this course provides the knowledge and experience needed to excel in the rapidly evolving field of deep learning.
What Will You Learn?
In the "Deep Learning" course, students will delve into the fundamentals and advanced concepts of neural networks and deep learning architectures. They will learn how to build and train deep neural networks, understand the principles of convolutional and recurrent neural networks, and explore advanced topics such as transfer learning, generative adversarial networks (GANs), and reinforcement learning. Through hands-on projects and real-world applications, students will gain practical experience in implementing deep learning models using popular frameworks like TensorFlow and PyTorch. The course will also cover techniques for optimizing and fine-tuning models to achieve high performance on complex datasets.
Requirements
> Computer
Audience
This course is ideal for data scientists, machine learning engineers, AI enthusiasts, and professionals in tech-related fields who want to deepen their understanding of deep learning and its applications. It is also suitable for students and researchers looking to enhance their skills in artificial intelligence and neural network modeling.
