Convolutional Neural Networks

This course is part of the Deep Learning Specialization

4.9
stars
38,168 ratings

Andrew Ng +2 more instructors
Top Instructors

Offered By

Deep Learning SpecializationDeepLearning.AI

About this Course

This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. 
You will:
- Understand how to build a convolutional neural network, including recent variations such as residual networks.
- Know how to apply convolutional networks to visual detection and recognition tasks.
- Know to use neural style transfer to generate art.
- Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data.

This is the fourth course of the Deep Learning Specialization.

Learner Career Outcomes

36%

started a new career after completing these courses

37%

got a tangible career benefit from this course

12%

got a pay increase or promotion

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 4 of 5 in the

Deep Learning Specialization

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 20 hours to complete

English

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

Skills you will gain

Facial Recognition SystemTensorflowConvolutional Neural NetworkArtificial Neural Network

Learner Career Outcomes

36%

started a new career after completing these courses

37%

got a tangible career benefit from this course

12%

got a pay increase or promotion

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 4 of 5 in the

Deep Learning Specialization

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 20 hours to complete

English

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

Instructors

Instructor rating

4.91/5 (2,132 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 Rating95%(55,581 ratings)

Week

Week 1

6 hours to complete

Foundations of Convolutional Neural Networks

Learn to implement the foundational layers of CNNs (pooling, convolutions) and to stack them properly in a deep network to solve multi-class image classification problems.

6 hours to complete

12 videos (Total 140 min), 4 readings, 3 quizzes

12 videos

Computer Vision5m

Edge Detection Example11m

More Edge Detection7m

Padding9m

Strided Convolutions9m

Convolutions Over Volume10m

One Layer of a Convolutional Network16m

Simple Convolutional Network Example8m

Pooling Layers10m

CNN Example12m

Why Convolutions?9m

Yann LeCun Interview27m

4 readings

Strided convolutions *CORRECTION*1m

Simple Convolutional Network Example *CORRECTION*1m

CNN Example *CORRECTION*1m

Why Convolutions? *CORRECTION*1m

1 practice exercise

The basics of ConvNets30m

Week

Week 2

5 hours to complete

Deep convolutional models: case studies

Learn about the practical tricks and methods used in deep CNNs straight from the research papers.

5 hours to complete

11 videos (Total 99 min), 1 reading, 2 quizzes

Week

Week 3

4 hours to complete

Object detection

Learn how to apply your knowledge of CNNs to one of the toughest but hottest field of computer vision: Object detection.

4 hours to complete

10 videos (Total 85 min), 2 readings, 2 quizzes

Week

Week 4

5 hours to complete

Special applications: Face recognition & Neural style transfer

Discover how CNNs can be applied to multiple fields, including art generation and face recognition. Implement your own algorithm to generate art and recognize faces!

5 hours to complete

11 videos (Total 76 min), 3 readings, 3 quizzes

11 videos

What is face recognition?4m

One Shot Learning4m

Siamese Network4m

Triplet Loss15m

Face Verification and Binary Classification6m

What is neural style transfer?2m

What are deep ConvNets learning?7m

Cost Function3m

Content Cost Function3m

Style Cost Function13m

1D and 3D Generalizations9m

3 readings

Triplet Loss *CORRECTION*1m

Face Verification and Binary Classification *CORRECTION*1m

Style Cost *CORRECTION*1m

1 practice exercise

Special applications: Face recognition & Neural style transfer30m

Reviews

4.9

4999 reviews

5 stars
87.57%
4 stars
10.51%
3 stars
1.45%
2 stars
0.28%
1 star
0.16%

TOP REVIEWS FROM CONVOLUTIONAL NEURAL NETWORKS

by RSDec 11, 2019

Great Course Overall One thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.

by RKSep 1, 2019

This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.

by AGJan 12, 2019

Great course for kickoff into the world of CNN's. Gives a nice overview of existing architectures and certain applications of CNN's as well as giving some solid background in how they work internally.

by OASep 3, 2020

Great course. Easy to understand and with very synthetized information on the most relevant topics, even though some videos repeat information due to wrong edition, everything is still understandable.

View all reviews

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.

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.

Convolutional Neural Networks

About this Course

Learner Career Outcomes

36%

37%

12%

Skills you will gain

Learner Career Outcomes

36%

37%

12%

Instructors

Andrew Ng
Top Instructor

Kian Katanforoosh
Top Instructor

Teaching Assistant - Younes Bensouda Mourri
Top Instructor

Offered by

DeepLearning.AI

Syllabus - What you will learn from this course

Week 1

Foundations of Convolutional Neural Networks

Week 2

Deep convolutional models: case studies

Week 3

Object detection

Week 4

Special applications: Face recognition & Neural style transfer

Reviews

TOP REVIEWS FROM CONVOLUTIONAL NEURAL NETWORKS

About the Deep Learning Specialization

Frequently Asked Questions

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Convolutional Neural Networks

About this Course

Learner Career Outcomes

36%

37%

12%

Skills you will gain

Learner Career Outcomes

36%

37%

12%

Instructors

Andrew NgTop Instructor

Kian KatanforooshTop Instructor

Teaching Assistant - Younes Bensouda MourriTop Instructor

Offered by

DeepLearning.AI

Syllabus - What you will learn from this course

Week 1

Foundations of Convolutional Neural Networks

Week 2

Deep convolutional models: case studies

Week 3

Object detection

Week 4

Special applications: Face recognition & Neural style transfer

Reviews

TOP REVIEWS FROM CONVOLUTIONAL NEURAL NETWORKS

About the Deep Learning Specialization

Frequently Asked Questions

Coursera Footer

Top Online Courses

Top Online Specializations

Online Certificates

Online Degree Programs

Coursera

Community

More

Andrew Ng
Top Instructor

Kian Katanforoosh
Top Instructor

Teaching Assistant - Younes Bensouda Mourri
Top Instructor