About this Course

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Learner Career Outcomes

39%

started a new career after completing these courses

38%

got a tangible career benefit from this course

11%

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Start instantly and learn at your own schedule.
Course 1 of 5 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 20 hours to complete
English
Subtitles: Chinese (Traditional), Arabic, French, Ukrainian, Chinese (Simplified), Portuguese (Brazilian), Vietnamese, Korean, Turkish, English, Spanish, Japanese...

Skills you will gain

Artificial Neural NetworkBackpropagationPython ProgrammingDeep Learning

Learner Career Outcomes

39%

started a new career after completing these courses

38%

got a tangible career benefit from this course

11%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 1 of 5 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 20 hours to complete
English
Subtitles: Chinese (Traditional), Arabic, French, Ukrainian, Chinese (Simplified), Portuguese (Brazilian), Vietnamese, Korean, Turkish, English, Spanish, Japanese...

Offered by

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deeplearning.ai

Syllabus - What you will learn from this course

Content RatingThumbs Up97%(158,547 ratings)Info
Week
1

Week 1

2 hours to complete

Introduction to deep learning

2 hours to complete
7 videos (Total 76 min), 2 readings, 1 quiz
7 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
2 readings
Frequently Asked Questions10m
How to use Discussion Forums10m
1 practice exercise
Introduction to deep learning30m
Week
2

Week 2

8 hours to complete

Neural Networks Basics

8 hours to complete
19 videos (Total 161 min), 7 readings, 3 quizzes
19 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
7 readings
Clarification about Upcoming Logistic Regression Cost Function Video1m
Clarification about Upcoming Gradient Descent Video1m
Derivation of DL/dz (optional reading)10m
Copy of Clarification about Upcoming Logistic Regression Cost Function Video1m
Clarification of "dz"10m
Deep Learning Honor Code2m
Programming Assignment FAQ10m
1 practice exercise
Neural Network Basics30m
Week
3

Week 3

5 hours to complete

Shallow neural networks

5 hours to complete
12 videos (Total 109 min), 2 readings, 2 quizzes
12 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
2 readings
Clarification: Activation Function1m
Clarification about Upcoming Backpropagation intuition (optional)1m
1 practice exercise
Shallow Neural Networks30m
Week
4

Week 4

5 hours to complete

Deep Neural Networks

5 hours to complete
8 videos (Total 64 min), 3 readings, 3 quizzes
8 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
3 readings
Clarification about Getting your matrix dimensions right video1m
Clarification about Upcoming Forward and Backward Propagation Video1m
Clarification about What does this have to do with the brain video1m
1 practice exercise
Key concepts on Deep Neural Networks30m

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About the Deep Learning Specialization

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

Frequently Asked Questions

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