Deep Learning Courses for Developers
8 courses on building with neural networks — the architecture behind modern AI, from image recognition to the large language models everyone now uses. They're hands-on and code-first, for developers who want to understand deep learning well enough to build and train networks themselves.
Deep learning is the engine under most of what's called AI today: layered neural networks that learn representations directly from data. These courses take you into how they actually work and how to build them — the structure of a network, how training adjusts it through backpropagation, and the main families such as convolutional networks for images and transformers for language and beyond. Expect to write code and work with frameworks rather than just read about the ideas. They suit developers who already have some programming footing and want to move from using AI to constructing the models underneath it — whether to specialize in it or to demystify what the large systems are doing.
Deep Learning courses
8 courses on the Develop AI track.
Advanced: Generative AI for Developers
Google Skills
Building AI Agents with Multimodal Models
NVIDIA Deep Learning Institute
Building Language Models on AWS
AWS Skill Builder
Elements of AI: Building AI
University of Helsinki & MinnaLearn
Google DeepMind: AI Research Foundations
Google Skills
Introduction to Deep Learning with PyTorch
DataCamp
Rapid Application Development with Large Language Models (LLMs)
NVIDIA Deep Learning Institute
The Art of Compressing LLMs: Pruning, Distillation, and Quantization
NVIDIA Deep Learning Institute
Frequently asked questions
- Is deep learning the same as machine learning?
- Deep learning is a branch of machine learning that uses multi-layered neural networks; it's especially good at learning from raw data like images, audio, and text, and it powers most of today's most capable AI systems.
- What background do I need for these deep learning courses?
- Programming ability is expected, and some comfort with the basics of machine learning and math like linear algebra helps — though several courses build the neural-network concepts up from the start for developers new to the area.
- Which frameworks do these courses use?
- Deep learning work is typically done in frameworks such as PyTorch or TensorFlow; the specific tools vary by course, so check each course's page to see what it teaches.
Key concepts
The foundational terms these courses build on — each chip links to a plain-English definition in the AI Pinnacle glossary.