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.
In this course, you will learn the foundations of deep learning. When you finish this class, you will:
- Understand the major technology trends driving Deep Learning
- Be able to build, train and apply fully connected deep neural networks
- Know how to implement efficient (vectorized) neural networks
- Understand the key parameters in a neural network's architecture
This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions.
This is the first course of the Deep Learning Specialization.
Ce cours fait partie de la Spécialisation Deep Learning
Neural Networks and Deep Learning
proposé par
À propos de ce cours
4.9
50,350 notes
Compétences que vous acquerrez
Artificial Neural NetworkBackpropagationPython ProgrammingDeep Learning
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
12 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.
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 learning20 min
Semaine
27 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.
19 vidéos (Total 161 min), 2 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
2 lectures
Deep Learning Honor Code2 min
Programming Assignment FAQ10 min
1 exercice pour s'entraîner
Neural Network Basics20 min
Semaine
35 heures pour terminer
Shallow neural networks
Learn to build a neural network with one hidden layer, using forward propagation and backpropagation.
12 vidéos (Total 109 min), 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
1 exercice pour s'entraîner
Shallow Neural Networks20 min
Semaine
45 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.
8 vidéos (Total 64 min), 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
1 exercice pour s'entraîner
Key concepts on Deep Neural Networks20 min
4.9
9,680 avis38%
a commencé une nouvelle carrière après avoir terminé ces cours
37%
a bénéficié d'un avantage concret dans sa carrière grâce à ce cours
11%
a obtenu une augmentation de salaire ou une promotion
Meilleurs avis
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!
I understand all those thing which you have discussed in this course and I also like the way first tell story of concet and assign assignment. Now I fall in love with neural network and deep learning.
Enseignants
Andrew Ng
CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain
Head Teaching Assistant - Kian Katanforoosh
Lecturer of Computer Science at Stanford University, deeplearning.ai, Ecole CentraleSupelec
Teaching Assistant - Younes Bensouda Mourri
Mathematical & Computational Sciences, Stanford University, deeplearning.aiÀ propos de deeplearning.ai
deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders.
À propos de la 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
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
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