Neural Networks and Deep Learning

This course is part of the Deep Learning Specialization

Top Instructors

4.9
stars
107,595 ratings
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21,480 reviews

975,546 already enrolled

Instructor(s): Andrew Ng +2 more

Subtitles: English, Chinese (Traditional),

Offered By

Deep Learning SpecializationDeepLearning.AI

About this Course

1,366,675 recent views

In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. 
By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications.

The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI.

Learner Career Outcomes

32%

started a new career after completing these courses

32%

got a tangible career benefit from this course

10%

got a pay increase or promotion

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 5 in the

Deep Learning Specialization

Intermediate Level

Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML

Approx. 23 hours to complete

English

Subtitles: Chinese (Traditional), Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Portuguese (Brazilian), Vietnamese, Korean, German, Russian, Turkish, English, Spanish, Japanese

Skills you will gain

Deep LearningArtificial Neural NetworkBackpropagationPython ProgrammingNeural Network Architecture

Learner Career Outcomes

32%

started a new career after completing these courses

32%

got a tangible career benefit from this course

10%

got a pay increase or promotion

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 5 in the

Deep Learning Specialization

Intermediate Level

Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML

Approx. 23 hours to complete

English

Instructors

Instructor rating

4.91/5 (18,195 Ratings)

Offered by

DeepLearning.AI

DeepLearning.AI is an education technology company that develops a global community of AI talent.

Syllabus - What you will learn from this course

Content Rating97%(186,792 ratings)

Week

Week 1

2 hours to complete

Introduction to Deep Learning

Analyze the major trends driving the rise of deep learning, and give examples of where and how it is applied today.

2 hours to complete

6 videos (Total 74 min), 2 readings, 1 quiz

Week

Week 2

8 hours to complete

Neural Networks Basics

Set up a machine learning problem with a neural network mindset and use vectorization to speed up your models.

8 hours to complete

19 videos (Total 161 min), 8 readings, 3 quizzes

19 videos

Binary Classification8m

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

8 readings

Connect with your Mentors and Fellow Learners on Discourse!10m

Derivation of DL/dz (Optional)10m

Clarification of "dz"10m

Lectures in PDF1m

Deep Learning Honor Code2m

Programming Assignment FAQ10m

How to Download your Notebook

How to Refresh your Workspace5m

1 practice exercise

Neural Network Basics20m

Week

Week 3

5 hours to complete

Shallow Neural Networks

Build a neural network with one hidden layer, using forward propagation and backpropagation.

5 hours to complete

12 videos (Total 109 min), 1 reading, 2 quizzes

12 videos

Neural Networks Overview4m

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

1 reading

Lectures in PDF1m

1 practice exercise

Shallow Neural Networks20m

Week

Week 4

8 hours to complete

Deep Neural Networks

Analyze the key computations underlying deep learning, then use them to build and train deep neural networks for computer vision tasks.

8 hours to complete

8 videos (Total 66 min), 5 readings, 3 quizzes

8 videos

Deep L-layer Neural Network5m

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?4m

5 readings

Clarification: What does this have to do with the brain?1m

Lectures in PDF1m

Confusing Output from the AutoGrader10m

References 10m

Acknowledgments10m

1 practice exercise

Key Concepts on Deep Neural Networks20m

Reviews

4.9

21480 reviews

5 stars
89.64%
4 stars
9.32%
3 stars
0.79%
2 stars
0.11%
1 star
0.11%

TOP REVIEWS FROM NEURAL NETWORKS AND DEEP LEARNING

by AAJul 2, 2020

Excellent course !!! The flow is perfect and is very easy to understand and follow the course\n\nI loved the simplicity with which Andrew explained the concepts. Great contribution to the community

by MCApr 21, 2019

This is a great course. The teaching quality and the standard of course materials clearly reflect the effort the instructors put in. As a result, I have increased my understanding of NN significantly.

by RGSep 6, 2020

I have learned a lot from this detailed and well-structured course. Programing assignments were very sophisticatedly designed. It was challenging, fun, and most importantly it delivered what is aimed.

by OOOct 20, 2017

Andrew Ng's presenting style is excellent. Makes the course easy to follow as it gradually moves from the basics to more advanced topics, building gradually. Very good starter course on deep learning.

View all reviews

About the Deep Learning Specialization

The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.

In this Specialization, you will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. Get ready to master theoretical concepts and their industry applications using Python and TensorFlow and tackle real-world cases such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more. AI is transforming many industries. The Deep Learning Specialization provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career. Along the way, you will also get career advice from deep learning experts from industry and academia.

Frequently Asked 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.
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.
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.

More questions? Visit the Learner Help Center.

Neural Networks and Deep Learning

About this Course

Learner Career Outcomes

32%

32%

10%

Skills you will gain

Learner Career Outcomes

32%

32%

10%

Instructors

Andrew Ng
Top Instructor

Kian Katanforoosh
Top Instructor

Younes Bensouda Mourri
Top Instructor

Offered by

DeepLearning.AI

Syllabus - What you will learn from this course

Week 1

Introduction to Deep Learning

Week 2

Neural Networks Basics

Week 3

Shallow Neural Networks

Week 4

Deep Neural Networks

Reviews

TOP REVIEWS FROM NEURAL NETWORKS AND DEEP LEARNING

About the Deep Learning Specialization

Frequently Asked Questions

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Neural Networks and Deep Learning

About this Course

Learner Career Outcomes

32%

32%

10%

Skills you will gain

Learner Career Outcomes

32%

32%

10%

Instructors

Andrew NgTop Instructor

Kian KatanforooshTop Instructor

Younes Bensouda MourriTop Instructor

Offered by

DeepLearning.AI

Syllabus - What you will learn from this course

Week 1

Introduction to Deep Learning

Week 2

Neural Networks Basics

Week 3

Shallow Neural Networks

Week 4

Deep Neural Networks

Reviews

TOP REVIEWS FROM NEURAL NETWORKS AND DEEP LEARNING

About the Deep Learning Specialization

Frequently Asked Questions

Coursera Footer

Start or advance your career

Browse popular topics

Upskill your team

Earn a degree or certificate online

Coursera

Community

More

Andrew Ng
Top Instructor

Kian Katanforoosh
Top Instructor

Younes Bensouda Mourri
Top Instructor