If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago.
Ce cours fait partie de la Spécialisation Deep Learning
Offert par
Spécialisation Deep Learningdeeplearning.aiÀ propos de ce cours
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Résultats de carrière des étudiants
39%
ont commencé une nouvelle carrière après avoir terminé ce cours
38%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
11%
a obtenu une augmentation de salaire ou une promotion
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 1 sur 5 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 20 heures pour terminer
Anglais
Sous-titres : Chinois (traditionnel), Arabe, Français, Ukrainien, Chinois (simplifié), Portugais (brésilien), Vietnamien, Coréen, Turc, Anglais, Espagnol, Japonais
Compétences que vous acquerrez
Artificial Neural NetworkBackpropagationPython ProgrammingDeep Learning
Résultats de carrière des étudiants
39%
ont commencé une nouvelle carrière après avoir terminé ce cours
38%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
11%
a obtenu une augmentation de salaire ou une promotion
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 1 sur 5 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 20 heures pour terminer
Anglais
Sous-titres : Chinois (traditionnel), Arabe, Français, Ukrainien, Chinois (simplifié), Portugais (brésilien), Vietnamien, Coréen, Turc, Anglais, Espagnol, Japonais
Offert par
deeplearning.ai
Founded by Andrew Ng, deeplearning.ai is on a mission to make world-class AI education accessible to people around the globe so that we can all benefit from an AI-powered future.
Programme du cours : ce que vous apprendrez dans ce cours
2 heures pour terminer
Introduction to deep learning
Be able to explain the major trends driving the rise of deep learning, and understand where and how it is applied today.
2 heures pour terminer
7 vidéos (Total 76 min), 2 lectures, 1 quiz
7 vidéos
Welcome5 min
What is a neural network?7 min
Supervised Learning with Neural Networks8 min
Why is Deep Learning taking off?10 min
About this Course2 min
Course Resources1 min
Geoffrey Hinton interview40 min
2 lectures
Frequently Asked Questions10 min
How to use Discussion Forums10 min
1 exercice pour s'entraîner
Introduction to deep learning30 min
8 heures pour terminer
Neural Networks Basics
Learn to set up a machine learning problem with a neural network mindset. Learn to use vectorization to speed up your models.
8 heures pour terminer
19 vidéos (Total 161 min), 6 lectures, 3 quiz
19 vidéos
Logistic Regression5 min
Logistic Regression Cost Function8 min
Gradient Descent11 min
Derivatives7 min
More Derivative Examples10 min
Computation graph3 min
Derivatives with a Computation Graph14 min
Logistic Regression Gradient Descent6 min
Gradient Descent on m Examples8 min
Vectorization8 min
More Vectorization Examples6 min
Vectorizing Logistic Regression7 min
Vectorizing Logistic Regression's Gradient Output9 min
Broadcasting in Python11 min
A note on python/numpy vectors6 min
Quick tour of Jupyter/iPython Notebooks3 min
Explanation of logistic regression cost function (optional)7 min
Pieter Abbeel interview16 min
6 lectures
Clarification about Upcoming Logistic Regression Cost Function Video1 min
Clarification about Upcoming Gradient Descent Video1 min
Derivation of DL/dz (optional reading)10 min
Clarification of "dz"10 min
Deep Learning Honor Code2 min
Programming Assignment FAQ10 min
1 exercice pour s'entraîner
Neural Network Basics30 min
5 heures pour terminer
Shallow neural networks
Learn to build a neural network with one hidden layer, using forward propagation and backpropagation.
5 heures pour terminer
12 vidéos (Total 109 min), 2 lectures, 2 quiz
12 vidéos
Neural Network Representation5 min
Computing a Neural Network's Output9 min
Vectorizing across multiple examples9 min
Explanation for Vectorized Implementation7 min
Activation functions10 min
Why do you need non-linear activation functions?5 min
Derivatives of activation functions7 min
Gradient descent for Neural Networks9 min
Backpropagation intuition (optional)15 min
Random Initialization7 min
Ian Goodfellow interview14 min
2 lectures
Clarification: Activation Function1 min
Clarification about Upcoming Backpropagation intuition (optional)1 min
1 exercice pour s'entraîner
Shallow Neural Networks30 min
5 heures pour terminer
Deep Neural Networks
Understand the key computations underlying deep learning, use them to build and train deep neural networks, and apply it to computer vision.
5 heures pour terminer
8 vidéos (Total 64 min), 3 lectures, 3 quiz
8 vidéos
Forward Propagation in a Deep Network7 min
Getting your matrix dimensions right11 min
Why deep representations?10 min
Building blocks of deep neural networks8 min
Forward and Backward Propagation10 min
Parameters vs Hyperparameters7 min
What does this have to do with the brain?3 min
3 lectures
Clarification about Getting your matrix dimensions right video1 min
Clarification about Upcoming Forward and Backward Propagation Video1 min
Clarification about What does this have to do with the brain video1 min
1 exercice pour s'entraîner
Key concepts on Deep Neural Networks30 min
Avis
Meilleurs avis pour RÉSEAU DE NEURONES ET DEEP LEARNING
par XL26 août 2017
This is a very good course for people who want to get started with neural networks. Andrew did a great job explaining the math behind the scenes. Assignments are well-designed too. Highly recommended.
par SS26 nov. 2017
Fantastic introduction to deep NNs starting from the shallow case of logistic regression and generalizing across multiple layers. The material is very well structured and Dr. Ng is an amazing teacher.
par JP11 févr. 2018
I would love some pointers to additional references for each video. Also, the instructor keeps saying that the math behind backprop is hard. What about an optional video with that? Otherwise, awesome!
par WY25 juin 2018
Really, really good course. Especially the tips of avoiding possible bugs due to shapes. Also impressed by the heroes' stories. Genuinely inspired and thoughtfully educated by Professor Ng. Thank you!
À propos du Spécialisation Deep Learning
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.
In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.
You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.
AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work.
We will help you master Deep Learning, understand how to apply it, and build a career in AI.
Foire Aux Questions
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
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