Acerca de este Curso
4.9
38,471 calificaciones
7,808 revisiones
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....
Globe

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Calendar

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Intermediate Level

Nivel intermedio

Clock

Approx. 16 hours to complete

Sugerido: 4 weeks of study, 3-6 hours a week...
Comment Dots

English

Subtítulos: English, Chinese (Traditional), Ukrainian, Chinese (Simplified), Portuguese (Brazilian), Korean, Turkish, Japanese...

Habilidades que obtendrás

Artificial Neural NetworkBackpropagationPython ProgrammingDeep Learning
Globe

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Calendar

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Intermediate Level

Nivel intermedio

Clock

Approx. 16 hours to complete

Sugerido: 4 weeks of study, 3-6 hours a week...
Comment Dots

English

Subtítulos: English, Chinese (Traditional), Ukrainian, Chinese (Simplified), Portuguese (Brazilian), Korean, Turkish, Japanese...

Programa - Qué aprenderás en este curso

Week
1
Clock
2 horas para completar

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. ...
Reading
7 videos (Total: 76 min), 2 readings, 1 quiz
Video7 videos
What is a neural network?7m
Supervised Learning with Neural Networks8m
Why is Deep Learning taking off?10m
About this Course2m
Course Resources1m
Geoffrey Hinton interview40m
Reading2 lecturas
Frequently Asked Questions10m
How to use Discussion Forums10m
Quiz1 ejercicio de práctica
Introduction to deep learning20m
Week
2
Clock
7 horas para completar

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. ...
Reading
19 videos (Total: 161 min), 2 readings, 3 quizzes
Video19 videos
Logistic Regression5m
Logistic Regression Cost Function8m
Gradient Descent11m
Derivatives7m
More Derivative Examples10m
Computation graph3m
Derivatives with a Computation Graph14m
Logistic Regression Gradient Descent6m
Gradient Descent on m Examples8m
Vectorization8m
More Vectorization Examples6m
Vectorizing Logistic Regression7m
Vectorizing Logistic Regression's Gradient Output9m
Broadcasting in Python11m
A note on python/numpy vectors6m
Quick tour of Jupyter/iPython Notebooks3m
Explanation of logistic regression cost function (optional)7m
Pieter Abbeel interview16m
Reading2 lecturas
Deep Learning Honor Code2m
Programming Assignment FAQ10m
Quiz1 ejercicio de práctica
Neural Network Basics20m
Week
3
Clock
5 horas para completar

Shallow neural networks

Learn to build a neural network with one hidden layer, using forward propagation and backpropagation. ...
Reading
12 videos (Total: 109 min), 2 quizzes
Video12 videos
Neural Network Representation5m
Computing a Neural Network's Output9m
Vectorizing across multiple examples9m
Explanation for Vectorized Implementation7m
Activation functions10m
Why do you need non-linear activation functions?5m
Derivatives of activation functions7m
Gradient descent for Neural Networks9m
Backpropagation intuition (optional)15m
Random Initialization7m
Ian Goodfellow interview14m
Quiz1 ejercicio de práctica
Shallow Neural Networks20m
Week
4
Clock
5 horas para completar

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. ...
Reading
8 videos (Total: 64 min), 3 quizzes
Video8 videos
Forward Propagation in a Deep Network7m
Getting your matrix dimensions right11m
Why deep representations?10m
Building blocks of deep neural networks8m
Forward and Backward Propagation10m
Parameters vs Hyperparameters7m
What does this have to do with the brain?3m
Quiz1 ejercicio de práctica
Key concepts on Deep Neural Networks20m
4.9
7,808 revisionesChevron Right
Direction Signs

38%

comenzó una nueva carrera después de completar estos cursos
Briefcase

83%

consiguió un beneficio tangible en su carrera profesional gracias a este curso
Money

10%

consiguió un aumento de sueldo o ascenso

Principales revisiones

por JPFeb 12th 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!

por MZSep 13th 2018

This course is really great.The lectures are really easy to understand and grasp.The assignment instructions are really helpful and one does not need to know python before hand to complete the course.

Instructores

Andrew Ng

Co-founder, Coursera; Adjunct Professor, Stanford University; formerly head of Baidu AI Group/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.ai

Acerca de deeplearning.ai

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

Acerca del programa especializado 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....
Deep Learning

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.