Deep Learning courses

Stanford University

Stanford CS229: Machine Learning I Spring 2022

This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionalit…

Harvard University

CS50AI: Introduction to AI with Python

Search, knowledge, probability, optimisation, machine learning and neural networks.

DeepLearning.AI

Advanced Learning Algorithms

In the second course of the Machine Learning Specialization, you will: • Build and train a neural network with TensorFlow to perform multi-class classification • Apply best practices for machine learning development so that your models generalize to data and tasks in the real world • Build and use…

DeepLearning.AI

Unsupervised Learning, Recommenders, Reinforcement Learning

In the third course of the Machine Learning Specialization, you will: • Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection. • Build recommender systems with a collaborative filtering approach and a content-based deep learning method. • Build a…

IBM

Deep Learning Fundamentals

Covers Data Science, Machine Learning, Deep Learning.

DeepLearning.AI

Custom Models, Layers, and Loss Functions with TensorFlow

In this course, you will: • Compare Functional and Sequential APIs, discover new models you can build with the Functional API, and build a model that produces multiple outputs including a Siamese network. • Build custom loss functions (including the contrastive loss function used in a Siamese netwo…

Stanford University

Stanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher Manning

Natural language processing (NLP) or computational linguistics is one of the most important technologies of the information age. Applications of NLP are everywhere because people communicate almost everything in language: web search, advertising, emails, customer service, language translation, virt…

Andrej Karpathy

Neural Networks: Zero to Hero

Great Learning

Introduction to Neural Networks and Deep Learning

This free Neural Networks and Deep Learning course gives valuable insights into deep learning applications in various fields and a better understanding of the different frameworks used in neural network applications. You will discover and understand various deep learning concepts and get familiariz…

Imperial College London

Customising your models with TensorFlow 2

Welcome to this course on Customising your models with TensorFlow 2! In this course you will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning models and workflows for any application. You will use lower level APIs in TensorFlow to develop complex…

Great Learning

Artificial Intelligence with Python

This Python with AI course provides a strong foundation in how neural networks work and how they are used to solve machine learning problems. You’ll learn the history behind neural networks, the link between biological and artificial neurons, and the core mechanics of perceptrons, dense networks, a…

Stanford University

Stanford CS229 Machine Learning | Spring 2026

This playlist features lectures from the Stanford graduate course CS229 Machine Learning. The course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative learning, parametric/non-parametric learning, neural networks);…

IBM

Deep Learning with TensorFlow

DeepLearning.AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the DeepLearning.AI TensorFlow Developer Specialization and will teach you best practices for using TensorFlow, a popular open-source…

IBM

AI Concepts

Covers Artificial Intelligence, Computer Vision, Deep Learning.

DeepLearning.AI

Structuring Machine Learning Projects

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies fo…

DeepLearning.AI

Sequence Models

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and t…

MIT OpenCourseWare

Introduction to Deep Learning

This is MIT’s introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concl…

Kaggle

Intro to Deep Learning

Neural networks with TensorFlow and Keras.

Kaggle

Computer Vision

Image classification with convolutional networks.