Hands-On Deep Learning with MIT OpenCourseWare

About this path

This learning path is based on MIT's 15.773 Hands-On Deep Learning course, taught by Rama Ramakrishnan. It is a fast-paced introduction that focuses on building practical skills for solving complex problems with unstructured data. You will start with the basics of deep neural networks and training, then move to convolutional networks for images, transformers for natural language, and finally generative models like large language models and text-to-image systems. Prior experience with Python and fundamental machine learning concepts is recommended.

What you will learn

• Understand the fundamentals of deep neural networks and how to train them.
• Build convolutional neural networks for image and video processing.
• Apply transfer learning and fine-tuning to computer vision tasks.
• Learn how to process natural language using embeddings and transformers.
• Explore generative AI, including large language models and text-to-image models.

Who this is for

Self-paced learners who want a clear free path with creator-credited YouTube lessons.

Curriculum