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Online Course

Neural Networks and Deep Learning

deeplearning.ai and Stanford University via Coursera

Overview

If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago.

In this course, you will learn the foundations of deep learning. When you finish this class, you will:
- Understand the major technology trends driving Deep Learning
- Be able to build, train and apply fully connected deep neural networks
- Know how to implement efficient (vectorized) neural networks
- Understand the key parameters in a neural network's architecture

This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions.

This is the first course of the Deep Learning Specialization.

Syllabus

Introduction to deep learning
-Be able to explain the major trends driving the rise of deep learning, and understand where and how it is applied today.

Neural Networks Basics
-Learn to set up a machine learning problem with a neural network mindset. Learn to use vectorization to speed up your models.

Shallow neural networks
-Learn to build a neural network with one hidden layer, using forward propagation and backpropagation.

Deep Neural Networks
-Understand the key computations underlying deep learning, use them to build and train deep neural networks, and apply it to computer vision.

Taught by

Andrew Ng

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Reviews

4.8 rating, based on 15 reviews

Start your review of Neural Networks and Deep Learning

  • Gregory J Hamel ( Life Is Study) completed this course and found the course difficulty to be easy.

    Neural Networks and Deep Learning is the first course in a new deep learning specialization offered by Coursera taught by Coursera founder Andrew Ng. The 4-week course covers the basics of neural networks and how to implement them in code using Python...
  • Cristi completed this course.

    I particularly enjoyed Andrew Ng's first course of the Deep Learning specialization because of its interactivity. Like any other programming course should be, we had to complete programming assignments as Jupyter Notebooks in the browser. We did not have...
  • Imaculate Mosha completed this course.

    It is designed for beginners in deep learning who have a background in basic python and linear algebra. Well planned, lets you develop intuitions about neural networks , also has optional video series on heroes of deep learning which is quite cool. People with some knowledge on NN might find it slow, but a good refresher. The Deep Learning specialization, which it is part of, is quite comprehensive too!
  • Ronny De Winter completed this course, spending 5 hours a week on it and found the course difficulty to be medium.

    The first excellent course of Andrew Ng's specialization on deep learning. WOW, this guy, the godfather of machine learning education (and co-founder of Coursera), knows how to educate the masses on one of the hottest technology topics in recent years....
  • Adail Muniz Retamal

    Adail Muniz Retamal completed this course, spending 4 hours a week on it and found the course difficulty to be medium.

    Having completed his classic Machine Learning course a few months earlier, I had all the concepts and intuitions still fresh in my mind, so I could go quickly through the lectures, quizzes and assignments. I really enjoyed it and highly recommend it for anyone interested on ML, Deep Learning and AI! I'm doing the entire specialization and couldn't be more satisfied!
  • Anonymous

    Anonymous completed this course.

    Its great ! It teaches you to build a simple neural network from scratch, the assigbments were very illustrative and it was a very good thing that the assignments are solved on the cloud using jupyter
    Notebooks without the need to download the data
  • Profile image for Vijayabhaskar
    Vijayabhaskar

    Vijayabhaskar completed this course, spending 4 hours a week on it and found the course difficulty to be medium.

    The Best Course on the internet to study about Artificial Neural Networks,you just need to know basic high school calculus and linear algebra to finish this course.Well structured and the programming assignments are so helpful!
  • David Raj Daniel completed this course.

    Great course. Builds the concepts step by step.
    End of the course have a good comfort of forward prop , back prop and build a shallow neural network and deep neural network using python numpy. Highly recommend for anyone pursuing deep learning
  • Daniel Rosquete completed this course, spending 4 hours a week on it and found the course difficulty to be medium.

    The course was good, Andrew NG is undoubtedly a great mind with too much knowledge, however, all the lessons were written on a white board. Is not that bad, but is not the easiest way to learn nevertheless.
  • Profile image for Raivis Joksts
    Raivis Joksts

    Raivis Joksts completed this course, spending 4 hours a week on it and found the course difficulty to be easy.

    I took this course with some prior background in the subject, including Python deep learning libraries. This is rather math (calculus) heavy course, but in order to understand the basic concepts and logic, and complete the course, one does not need to fully understand how formulas work - just what is the objective of using this step or that step in the algorithm. Overall, one of the best introductory materials on deep learning. For those still struggling I recommend to star with Khan's Academy intro lectures on deep learning.
  • Anonymous

    Anonymous completed this course.

    Great course! I really liked how systematically Andrew Ng goes through this broad field. You probably won't learn everything there is in the real of Deep Learning just by taking this course (I think that would be impossible) but you will get a rock solid (trusted) foundation for the important parts to expand that knowledge and keep up with latest progress on your own afterwards.
  • Anonymous

    Anonymous completed this course.

    Great introduction to the nuts and bolts of neural networks. Not math intensive but enough to give you more than an intuition of what’s happening under the hood. Notebooks with boilerplate code allow for targeted and efficient learning.
  • Chaitanya Kale completed this course, spending 4 hours a week on it and found the course difficulty to be easy.

    It's a great course to understand basics of deep learning with a detailed walkthrough of gradient descent algorithm, forward propagation, backward propagation, cost and activation functions with logistic regression as a starting point.
  • Anonymous

    Anonymous completed this course.

    Totally enjoyed this class! I consider Andrew Ng one of the best instructors in this field. The class will actually have you write code weekly and your own deep neural network. Highly recommend it.
  • Uğur Kaplan

    Uğur Kaplan is taking this course right now, spending 4 hours a week on it and found the course difficulty to be medium.

    It is good course even though there is redundancy in it. I guess Andrew Ng repeats the concepts he finds important so students can understand. But that much repetition kills the flow, in my opinion.

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