This course is part of the Deep Learning Specialization

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Andrew Ng +2 more instructors

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Deep Learning SpecializationDeepLearning.AI

About this Course

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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.

Flexible deadlines

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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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. 24 hours to complete

English

Skills you will gain

Deep Learning
Artificial Neural Network
Backpropagation
Python Programming
Neural Network Architecture

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.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

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. 24 hours to complete

English

Instructors

Instructor rating

4.91/5 (21,789 Ratings)

Offered by

DeepLearning.AI

Syllabus - What you will learn from this course

Content Rating97%(205,082 ratings)

Week1

Week 1

3 hours to complete

Introduction to Deep Learning

3 hours to complete

6 videos (Total 74 min), 1 reading, 4 quizzes

Week2

Week 2

8 hours to complete

Neural Networks Basics

8 hours to complete

19 videos (Total 161 min), 5 readings, 4 quizzes

19 videos

Binary Classification8mLogistic Regression5mLogistic Regression Cost Function8mGradient Descent11mDerivatives7mMore Derivative Examples10mComputation Graph3mDerivatives with a Computation Graph14mLogistic Regression Gradient Descent6mGradient Descent on m Examples8mVectorization8mMore Vectorization Examples6mVectorizing Logistic Regression7mVectorizing Logistic Regression's Gradient Output9mBroadcasting in Python11mA Note on Python/Numpy Vectors6mQuick tour of Jupyter/iPython Notebooks3mExplanation of Logistic Regression Cost Function (Optional)7mPieter Abbeel Interview16m

5 readings

Derivation of DL/dz (Optional)10mDeep Learning Honor Code2mProgramming Assignment FAQ10mHow to Download your NotebookHow to Refresh your Workspace5m

1 practice exercise

Neural Network Basics 50m

Week3

Week 3

6 hours to complete

Shallow Neural Networks

6 hours to complete

12 videos (Total 109 min)

12 videos

Neural Networks Overview4mNeural Network Representation5mComputing a Neural Network's Output9mVectorizing Across Multiple Examples9mExplanation for Vectorized Implementation7mActivation Functions10mWhy do you need Non-Linear Activation Functions?5mDerivatives of Activation Functions7mGradient Descent for Neural Networks9mBackpropagation Intuition (Optional)15mRandom Initialization7mIan Goodfellow Interview14m

1 practice exercise

Shallow Neural Networks50m

Week4

Week 4

9 hours to complete

Deep Neural Networks

9 hours to complete

8 videos (Total 64 min), 5 readings, 4 quizzes

8 videos

Deep L-layer Neural Network5mForward Propagation in a Deep Network7mGetting your Matrix Dimensions Right11mWhy Deep Representations?10mBuilding Blocks of Deep Neural Networks8mForward and Backward Propagation10mParameters vs Hyperparameters7mWhat does this have to do with the brain?3m

5 readings

Optional Reading: Feedforward Neural Networks in Depth10mClarification For: What does this have to do with the brain?1mConfusing Output from the AutoGrader10mReferences 10mAcknowledgments10m

1 practice exercise

Key Concepts on Deep Neural Networks50m

Reviews

4.9

23261 reviews

5 stars
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4 stars
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3 stars
0.80%
2 stars
0.12%
1 star
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TOP REVIEWS FROM NEURAL NETWORKS AND DEEP LEARNING

by LVApr 6, 2019

A bit easy (python wise) but maybe that's just a reflection of personal experience / practice. The contest is easy to digest (week to week) and the intuitions are well thought of in their explanation.

by SSNov 26, 2017

Fantastic introduction to deep NNs starting from the shallow case of logistic regression and generalizing across multiple layers. The material is very well structured and Dr. Ng is an amazing teacher.

by ZRJan 3, 2020

At first, I want to thank the course teacher and all the others for providing us such a wonderful course. The way the professor teaches is really very very helpful. Thank you all again and keep it up.

by NTJan 17, 2020

Very structured approach to developing a neural network which I believe I can use as foundation for any project regardless its complexity. Thanks professor Andrew Ng and the team for their dedication.

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. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

Neural Networks and Deep Learning

About this Course

Skills you will gain

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

Introduction to Deep Learning

Neural Networks Basics

Shallow Neural Networks

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

Skills you will gain

Instructors

Andrew NgTop Instructor

Kian KatanforooshTop Instructor

Younes Bensouda MourriTop Instructor

Offered by

DeepLearning.AI

Syllabus - What you will learn from this course

Introduction to Deep Learning

Neural Networks Basics

Shallow Neural Networks

Deep Neural Networks

Reviews

TOP REVIEWS FROM NEURAL NETWORKS AND DEEP LEARNING

About the Deep Learning Specialization

Frequently Asked Questions

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Andrew Ng
Top Instructor

Kian Katanforoosh
Top Instructor

Younes Bensouda Mourri
Top Instructor