Des neurones à la psyché, Introduction aux réseaux de neurones biologiques et artificiels (FUN)

Coursera

University of Washington

Machine Teaching for Autonomous AI (Coursera)

Engineering

Just as teachers help students gain new skills, the same is true of artificial intelligence (AI). Machine learning algorithms can adapt and change, much like the learning process itself. Using the machine teaching paradigm, a subject matter expert (SME) can teach AI to improve and optimize a variety of systems and processes. The result is an autonomous AI system.

Sep 7th 2026

4 Weeks

Artificial Intelligence Machine Learning Neural Networks

Details

Coursera

Duke University

Introduction to Machine Learning (Coursera)

Data Science

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction.

Aug 24th 2026

5-12 Weeks

ML NLP Machine Learning

Details

EdX

HarvardX,Harvard University

Fundamentals of Neuroscience, Part 1: The Electrical Properties of the Neuron (edX)

Sci: Biology & Life Sciences

Learn how electricity makes the neurons in your brain tick. Fundamentals of Neuroscience is a three-courseseries that explores the structure and function of the nervous system—from the inner workings of a single nerve cell to the staggering complexity of the brain and the social interactions they enable.

Self Paced

Self-Paced

Neuroscience Brain Bioelectricity

Details

EdX

HarvardX,Harvard University

Fundamentals of Neuroscience, Part 2: Neurons and Networks (edX)

Sci: Biology & Life Sciences

Discover what makes your brain tick in this second part of a four-part introductory series in Neuroscience. Neurons in isolation are fascinating and complicated, but the real magic of neuroscience happens in the interaction between neurons. In this course, we examine how neurons pass signals to one another and how complex dynamics can result from just a few neurons arranged in relatively simple circuits.

Self Paced

Self-Paced

Neuroscience Biology Brain

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FUN

Aix-Marseille Université

Cellular neurophysiology: how neurons communicate (FUN)

Sci: Biology & Life Sciences

How does information circulate in the nervous system? How is the universal language of neurons, the action potential, generated? How does it travel along axons? And how does it influence other neurons? Thanks to this MOOC, you will master these basic principles of neuronal physiology.

Oct 5th 2021

5-12 Weeks

Neurons Cellular Neurophysiology Neuronal Physiology

Details

FUN

CY Cergy Paris Université

S'initier à la Data Science et à ses enjeux (FUN)

CS: Programming Data Science

La Data Science d’un monde qui change ! La Big data, et plus généralement l’analyse de données, occupent une place de plus en plus importante au sein des stratégies de nombreuses organisations. Suivi de performance, analyse des comportements, découvertes de nouvelles opportunités de marché : les applications sont multiples, et intéressent des secteurs variés. Du e-commerce à la finance, en passant par les transports et la santé, les entreprises ont besoin de talents formés à la collecte, au stockage, mais aussi au traitement et à la modélisation des données.

Self Paced

Self-Paced

Artificial Intelligence Machine Learning Big Data

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Coursera

IBM

Deep Learning and Reinforcement Learning (Coursera)

Data Science

This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. First you will learn about the theory behind Neural Networks, which are the basis of Deep Learning, as well as several modern architectures of Deep Learning.

Aug 31st 2026

5-12 Weeks

Calculus Python Statistics

Details

Coursera

Illinois Tech

Statistical Learning (Coursera)

Statistics & Data Analysis Data Science

This course offers a deep dive into the world of statistical analysis, equipping learners with cutting-edge techniques to understand and interpret data effectively. We explore a range of methodologies, from regression and classification to advanced approaches like kernel methods and support vector machines, all designed to enhance your data analysis skills.

Sep 14th 2026

5-12 Weeks

Classification Linear Regression Logistic Regression

Details

Coursera

DeepLearning.AI

Natural Language Processing with Probabilistic Models (Coursera)

Data Science

In Course 2 of the Natural Language Processing Specialization, offered by deeplearning.ai, you will: a) Create a simple auto-correct algorithm using minimum edit distance and dynamic programming; b) Apply the Viterbi Algorithm for part-of-speech (POS) tagging, which is important for computational linguistics, c) Write a better auto-complete algorithm using an N-gram language model, and d) Write your own Word2Vec model that uses a neural network to compute word embeddings using a continuous bag-of-words model.

Aug 24th 2026

4 Weeks

NLP Machine Learning Neural Networks

Details

Coursera

Universidad Austral

Optimización de Redes Neuronales Profundas (Coursera)

Security & Networking

Este curso se centrará en la optimización de Redes Neuronales Profundas, cambiando la idea de que todo el proceso es una “caja negra”. Comprenderá qué impulsa el rendimiento y podrá obtener mejores resultados de manera más sistemática. Entenderá cómo optimizar los principales Hiperparámetros y su implementación. Además, aprenderá nuevos conceptos útiles para el entrenamiento de las redes como los mini-batch y las regularizaciones. También, aprenderá a implementar una red neuronal utilizando TensorFlow

Aug 31st 2026

3 Weeks

Neural Networks Optimization TensorFlow

Details

Coursera

University of Washington

Computational Neuroscience (Coursera)

Robotics & Computer Vision

This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning.

Sep 14th 2026

5-12 Weeks

Neuroscience MATLAB Brain

Details

Coursera

Hebrew University of Jerusalem

Synapses, Neurons and Brains (Coursera)

Sci: Biology & Life Sciences Health & Society

These are very unique times for brain research. The aperitif for the course will thus highlight the present “brain-excitements” worldwide. You will then become intimately acquainted with the operational principles of neuronal “life-ware” (synapses, neurons and the networks that they form) and consequently, on how neurons behave as computational microchips and how they plastically and constantly change - a process that underlies learning and memory.

Aug 24th 2026

5-12 Weeks

Health Biology Brain

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