Deep Learning Specialization
Andrew Ng's foundational five-course series on neural networks, sequence models, and structuring ML projects.
What you'll learn
- Build and train deep neural networks from scratch
- Implement convolutional networks for image tasks
- Apply recurrent networks and transformers to sequence data
- Structure ML projects to avoid common pitfalls
- Read and reproduce results from research papers
About this course
The single most cited entry point to deep learning. Andrew Ng walks you through the math, the intuition, and the engineering of modern neural networks. By the end you'll understand convolutional networks for vision, recurrent networks for sequences, and how to structure ML projects so they actually ship. Honest assessment: dense, occasionally dated on the very newest models, but unmatched for foundational understanding.
Prerequisites
Comfortable with Python and basic linear algebra. No prior ML required.