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Course Description

  • What are the course objectives?

    Deep Learning is one of the most exciting and promising segments of Artificial Intelligence and machine learning technologies. This deep learning course with TensorFlow is designed to help you master deep learning techniques and build deep learning models using TensorFlow, the open-source software library developed by Google for the purpose of conducting machine learning and deep neural networks research. It is one of the most popular software platforms used for deep learning and contains powerful tools to help you build and implement artificial neural networks.
     
    Advancements in deep learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in deep learning models, learn to operate TensorFlow to manage neural networks and interpret the results.
     
    And according to payscale.com, the median salary for engineers with deep learning skills tops $120,000 per year.
     
    What are the course objectives

  • What skills will you learn with this Deep Learning course?

    By the end of this deep learning course with TensorFlow, you will be able to accomplish the following:

    • Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
    • Implement deep learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before
    • Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
    • Build deep learning models in TensorFlow and interpret the results
    • Understand the language and fundamental concepts of artificial neural networks
    • Troubleshoot and improve deep learning models
    • Build your own deep learning project
    • Differentiate between machine learning, deep learning and artificial intelligence

  • Who should take this Deep Learning with TensorFlow course?

    There is booming demand for skilled deep learning engineers across a wide range of industries, making this deep learning course with TensorFlow training well-suited for professionals at the intermediate to advanced level of experience. We recommend this deep learning online course particularly for the following professionals: 
    • Software engineers
    • Data scientists
    • Data analysts
    • Statisticians with an interest in deep learning

  • What projects are included in this Deep Learning Online Training Course?

    The course includes the following industry-based project. Successful evaluation of the following project is a part of the certification eligibility criteria:

    Project 1: Pet Classification Model Using CNN

    In this project, you build a CNN model that classifies the given pet images correctly into dog and cat images. The code template is given with essential code blocks. TensorFlow can be used to train the data and calculate the accuracy score on the test data.

  • What are the prerequisites for this Deep Learning online course?

    Participants in this Deep Learning online course should have:

    • Familiarity with programming fundamentals
    • Fair understanding of basics of statistics and mathematics

Course Preview

  • Deep Learning with TensorFlow

    • 1. Introduction to TensorFlow

      • Intro to TensorFlow
      • Computational Graph
      • Key highlights
      • Creating a Graph
      • Regression example
      • Gradient Descent
      • TensorBoard
      • Modularity
      • Sharing Variables
      • Keras

    • 2. Perceptrons

      43:03
      • What is a Perceptron
        43:03
      • XOR Gate

    • 3. Activation Functions

      20:52
      • Sigmoid
      • ReLU
        15:20
      • Hyperbolic Fns
        05:32
      • Softmax

    • 4. Artificial Neural Networks

      1:13:08
      • Introduction
        59:50
      • Perceptron Training Rule
        13:18
      • Gradient Descent Rule

    • 5. Gradient Descent and Backpropagation

      59:30
      • Gradient Descent
        59:30
      • Stochastic Gradient Descent
      • Backpropagation
      • Some problems in ANN

    • 6. Optimization and Regularization

      • Overfitting and Capacity
      • Cross Validation
      • Feature Selection
      • Regularization
      • Hyperparameters

    • 7. Intro to Convolutional Neural Networks

      • Intro to CNNs
      • Kernel filter
      • Principles behind CNNs
      • Multiple Filters
      • CNN applications

    • 8. Introduction to Recurrent Neural Networks

      • Introduction to RNNs
      • Unfolded RNNs
      • Seq2Seq RNNs
      • LSTM
      • RNN applications

    • 9. Deep Learning applications

      • Image Processing
      • Natural Language Processing
      • Speech Recognition
      • Video Analytics
  • Free Course

    Math Refresher

    • Math Refresher

      30:36
      • Math Refresher
        30:36
  • Free Course

    Deep Learning Fundamentals

    • Lesson 1 - Learning Objectives

      • Learning Objectives

    • Lesson 2 - Introduction to Deep Learning

      22:31
      • Learning Objectives
      • 1.1 Deep Learning: The Series Introduction
        03:46
      • 1.2 What is a Neural Network
        06:28
      • 1.3 Three Reasons to go Deep
        03:56
      • 1.4 Your choice of Deep Net
        02:58
      • 1.5 An Old Problem
        05:23

    • Lesson 3 - Deep Learning Models

      22:56
      • Learning Objectives
      • 2.1 Restricted Boltzmann Machines
        04:50
      • 2.2 Deep Belief Nets
        04:31
      • 2.3 Convolutional Nets
        08:15
      • 2.4 Recurrent Nets
        05:20

    • Lesson 4 - Additional Deep Learning Models

      19:13
      • Learning Objectives
      • 3.1 Autoencoders
        03:51
      • 3.2 Recursive Neural Tensor Nets
        05:49
      • 3.3 Use Cases
        09:33

    • Lesson 5 - Deep Learning Platforms & Libraries

      25:37
      • Learning Objectives
      • 4.1 What is a Deep Net Platform?
        03:41
      • 4.2 H2O.ai
        03:42
      • 4.3 Dato GraphLab
        03:32
      • 4.4 What is a Deep Learning Library?
        01:58
      • 4.5 Theano
        03:21
      • 4.6 Caffe
        02:48
      • 4.7 Tensorflow
        06:35
      • Unlocking IBM Certificate
  • Free Course

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Exam & Certification

  • What do I need to do to unlock my Simplilearn certificate?

    To obtain the Deep Learning with TensorFlow certification for Online Classroom, you will need to:
    • Attend one complete batch
    • Complete and attain evaluation of any one of the given projects

  • Who provides the certification and how long is it valid for?

    Upon successful completion of the Deep Learning online training course, you will be awarded an industry-recognized course completion certificate from Simplilearn which has a lifelong validity.

  • What are the system requirements to attend the training sessions?

    Minimum system requirements for attending this course are-

    • 8 core processor
    • 32 GB RAM

Course Advisor

Mike Tamir
Mike Tamir No. 1 AI and Machine Learning Influencer, Head of Data Science - Uber ATG

​Named by Onalytica as the No.1 influencer in AI and Machine Learning space, Mike serves as Head of Data Science for Uber ATG self-driving engineering team and as UC Berkeley data science faculty.

Reviews

A.Anthony Davis
A.Anthony Davis Kingston

The Simplilearn Data Scientist Master’s Program is an awesome course! You learn how to solve real-world problems, and the wide variety of projects give you hands-on experience to make you industry-ready. The lecturers are experts and share their knowledge energetically. Thank you for an excellent learning experience.

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Abhishek Tripathi
Abhishek Tripathi Bangalore

Good online content for data science. I completed Data Science with R and Python. The instructors have good knowledge on the subject. Self-learning videos help a lot, too. Thanks, Simplilearn.

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Angiras Modak
Angiras Modak Associate System Engineer at IBM India Pvt. Ltd., Kolkata

Simplilearn is one of the best online training providers available. The trainer was really great in explaining the concepts to the minute detail and also gave multiple real-world examples. The course content was very informative. I understood the concept of CNN. Overall I really enjoyed the training a lot.

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    FAQs

    • What if I miss a class?

      Simplilearn provides recordings of each class so you can review them as needed before the next session. With Flexi-pass, Simplilearn gives you access to all classes for 90 days so that you have the flexibility to choose sessions as per your convenience.

    • Who are the instructors and how are they selected?

      All of our highly qualified trainers are industry experts with years of relevant industry experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating remain on our faculty.

    • How will the labs be conducted?

      Simplilearn provides Integrated labs for all the hands-on and projects execution. The learners will be guided on all aspects, from deploying tools to executing hands-on exercises.

    • What is Global Teaching Assistance?

      Our teaching assistants are a dedicated team of subject matter experts here to help you get certified in your first attempt. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours.  

    • Is this live training or will I watch pre-recorded videos?

      The Deep Learning online training is conducted through live streaming. They are interactive sessions that enable you to ask questions and participate in discussions during class time. We do, however, provide recordings of each session you attend for your future reference. Classes are attended by a global audience to enrich your learning experience.

    • What is covered under the 24/7 Support promise?

      We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your course with us.

    • What is Online Classroom training?

      All of the classes are conducted via live online streaming. They are interactive sessions that enable you to ask questions and participate in discussions during class time.

    • Do you provide a money back guarantee for the training programs?

      Yes. We do offer a money-back guarantee for many of our training programs. Refer to our Refund Policy and submit refund requests via our Help and Support portal.

    • How do I enrol for the online training?

      You can enrol for this Deep Learning online training on our website and make an online payment using any of the following options: 
      • Visa Credit or Debit Card
      • MasterCard
      • American Express
      • Diner’s Club
      • PayPal
      Once payment is received you will automatically receive a payment receipt and access information via email.

    • If I need to cancel my enrollment, can I get a refund?

      Yes, you can cancel your enrollment if necessary. We will refund the course price after deducting an administration fee. To learn more, please read our Refund Policy.
       

    • How can I learn more about this training program?

      Contact us using the form on the right of any page on the Simplilearn website, or select the Live Chat link. Our customer service representatives can provide you with more details.
       

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    Contact Us

    +1-844-532-7688

    (Toll Free)

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    • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.
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