This course is part of the Deep Learning Specialization

4.9
stars
117,435 ratings

Andrew Ng +2 more instructors

Top Instructors

1,151,346 already enrolled

Offered By

Deep Learning SpecializationDeepLearning.AI

About this Course

1,038,040 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.

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. 25 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.

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. 25 hours to complete

English

Instructors

Instructor rating

4.91/5 (21,644 Ratings)

Offered by

DeepLearning.AI

Syllabus - What you will learn from this course

Content Rating97%(203,869 ratings)

Week

Week 1

3 hours to complete

Introduction to Deep Learning

3 hours to complete

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

Week

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 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

5 readings

Derivation of DL/dz (Optional)10m

Deep Learning Honor Code2m

Programming Assignment FAQ10m

How to Download your Notebook

How to Refresh your Workspace5m

1 practice exercise

Neural Network Basics 50m

Week

Week 3

6 hours to complete

Shallow Neural Networks

6 hours to complete

12 videos (Total 109 min)

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 practice exercise

Shallow Neural Networks50m

Week

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 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?3m

5 readings

Optional Reading: Feedforward Neural Networks in Depth10m

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

Confusing Output from the AutoGrader10m

References 10m

Acknowledgments10m

1 practice exercise

Key Concepts on Deep Neural Networks50m

Reviews

4.9

23175 reviews

5 stars
89.72%
4 stars
9.21%
3 stars
0.80%
2 stars
0.12%
1 star
0.13%

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

I loved the simplicity with which Andrew explained the concepts. Great contribution to the community

by AHApr 29, 2020

Amazing course, the lecturer breaks makes it very simple and quizzes, assignments were very helpful to ensure your understanding of the content. Hope for future learners you provide code model-answers

by AKMay 13, 2020

One of the best courses I have taken so far. The instructor has been very clear and precise throughout the course. The homework section is also designed in such a way that it helps the student learn .

by STJul 6, 2018

I think the course explains the underlying concepts well and even if you are already familiar with deep neural networks it's a great complementary course for any pieces you may have missed previously.

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

Start or advance your career

Popular Courses and Certifications

Popular collections and articles

Earn a degree or certificate online

Coursera

Community

More

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

Coursera Footer

Start or advance your career

Popular Courses and Certifications

Popular collections and articles

Earn a degree or certificate online

Coursera

Community

More

Andrew Ng
Top Instructor

Kian Katanforoosh
Top Instructor

Younes Bensouda Mourri
Top Instructor