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Deep Learning

Amazon , Amazon Web Services and Facebook via Udacity Nanodegree


Learn to leverage the capabilities of deep learning tools to fix complex problems and unlock next-level results for enterprises.


  • Introduction to Deep Learning
    • Begin by learning the fundamentals of deep learning. Then examine the foundational algorithms underpinning modern deep learning: gradient descent and backpropagation. Once those foundations are established, explore design constructs of neural networks and the impact of these design decisions. Finally, the course explores how neural network training can be optimized for accuracy and robustness.
  • Convolutional Neural Networks
    • This course introduces convolutional neural networks, the most widely used type of neural networks specialized in image processing. You will learn the main characteristics of CNNs that make them better than standard neural networks for image processing. Then you’ll examine the inner workings of CNNs and apply the architectures to custom datasets using transfer learning. Finally, you will learn how to use CNNs for object detection and semantic segmentation.
  • RNNs & Transformers
    • This course covers multiple RNN architectures and discusses design patterns for those models. Additionally, you’ll focus on the latest transformer architectures.
  • Building Generative Adversarial Networks
    • Become familiar with generative adversarial networks (GANs) by learning how to build and train different GANs architectures to generate new images. Discover, build, and train architectures such as DCGAN, CycleGAN, ProGAN, and StyleGAN on diverse datasets including the MNIST dataset, Summer2Winter Yosemite dataset, or CelebA dataset.

Taught by

Mat Leonard, Luis Serrano, Cezanne Camacho, Alexis Cook, Jennifer Staab, Sean Carrell, Ortal Arel, Jay Alammar, Vyom S., Peter L., Nohemy V., Sebastian P., Karim B. and Harshit A.


4.7 rating, based on 16 Class Central reviews

Start your review of Deep Learning

  • I am a Mentor for this course. I find this course one of the best courses in the internet. It is the only course that is provided from Facebook, which is the main contributor of the PyTorch. It has a lot of notebooks and videos to learn with visualizations. The deep learning is in its whole spectrum with computer vision, nlp and machine learning projects, that shows the big change it brought to these domains.
  • Anonymous
    Could use a lot of work: not yet worth the money A lot of effort has clearly gone into this course and I believe it may be worthwhile doing at some point, but unfortunately isn't yet worthwhile. The materials are a mix-up of different components merged...
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    Jonathan Yeh
    The program is great. It teaches deep learning from scratch.

    The most exciting part is that you do feel equipped with the skills and techniques covered when you proceed. The project review is awesome. You can see the thorough review in detail. It renews the knowledge learned and properly bridges the complex concept to code implementation.

    In addition, we can see additional resources mentioned in the feedback. That's really informative. Thanks and really appreciate that.
  • Anonymous
    This course helps in improving your understanding. The projects are designed to feel the taste of real-time scenarios. This definitely helps you to practice more and more, till you reach a level of expertise.
  • Good start point
    The course is a good start point in Deep Learning, but I feel that it could have more theory on some topics. It uses TensorFlow in almost all projects.
  • Anonymous
    Very good introduction to Deep Learning
  • Project-oriented
  • Anonymous
    BEST INTRO TO DEEP LEARNING BEST INTRO FOR PEOPLE WITH LITTLE OR NO DEEP LEARNING EXPERIENCE START The best thing about the course is the first section. It takes a simple prediction problem, "If grades= something, age=something then will X get accepted...
  • Michael Gruben-trejo
    Good Intro for people with Little or no Deep Learning Experience This ND starts by covering the mathematical foundations of Deep Learning, then moves you through some interesting types of Deep Learning networks and their applications. The ND uses TensorFlow...
  • Anonymous
    Good stepping stone to a deep learning career.
    The lectures are more breadth-focused than depth. Acts as a good introduction to a lot of the deep learning concepts. It is left on the student to explore all the concepts in greater detail, which is mandatory if anyone wants to make a career in this field. The slack channel is an amazing place to communicate with other DL enthusiasts and the office hours with experts gives an insight into how people are actually applying neural nets in research. The projects and mini-projects are the best part of the course as they'll really give your resume a boost if you work hard on them. Overall, highly recommended.
  • Anonymous
    Good starting point for deep learning
    This course will teach you all the basics and some advance methods of deep learning. I highly recommend it if you're interested in machine learning in general.
    Projects are well designed although a little cookie-cutter. The course uses Python which is easy to learn if you haven't used it before. A bit of knowledge about machine learning helps breeze trough the content and understand more advance concepts, although it's not required.
  • Anonymous
    Good experience overall, but intensive!
    It's a great overview of deep learning, with significant project experience in TensorFlow and numpy. My only complaint is that it took much more time each week than initially advertised. The projects were really helpful.
  • A great way to learn deep learning
    The course does a wonderful job of keeping you motivated and helping you along the way. The production quality is second to none, and you learn everything from the ground up.
  • Ravi Chandra
    Best course available out there!
    With the new added content deep learning nanodegree can be very powerful in terms of learning. Got a job just one week after graduating from it as a fresher. So much to learn.
  • Anonymous

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