Deep Learning Course Overview

In this Deep Learning with Keras and TensorFlow course, you will become familiar with the language and fundamental concepts of artificial neural networks, PyTorch, autoencoders, and more. Upon completion, you will be able to build deep learning models, interpret results and build your own deep learning project.

Tensorflow Training Key Features

100% Money Back Guarantee
No questions asked refund*

At Simplilearn, we value the trust of our patrons immensely. But, if you feel that a course does not meet your expectations, we offer a 7-day money-back guarantee. Just send us a refund request via email within 7 days of purchase and we will refund 100% of your payment, no questions asked!
  • 34 hours of Blended Learning
  • Real-life industry-based projects
  • 24/7 support with dedicated project mentoring sessions
  • Flexibility to choose classes
  • Dedicated mentoring session from our Industry expert faculties

Skills Covered

  • Keras and TensorFlow Framework
  • PyTorch and its elements
  • Image Classification
  • Artificial Neural Networks
  • Autoencoders
  • Deep Neural Networks
  • Conventional Neural Networks
  • Recurrent Neural Networks
  • ADAM Adagrad and Momentum

Benefits

Deep learning is one of the latest technologies in AI and machine learning, used in smartphone apps, power grids, helping us find solutions to climate change, and more. This course can lead to lucrative roles in IT, healthcare, FinTech, e-commerce, and other industries.

  • Designation
  • Annual Salary
  • Hiring Companies
  • Annual Salary
    472KMin
    1,194KAverage
    2,212KMax
    Source: Glassdoor
    Hiring Companies
    Amazon
    IBM
    Microsoft
    Source: Indeed
  • Annual Salary
    463KMin
    813KAverage
    1,581KMax
    Source: Glassdoor
    Hiring Companies
    Google
    American Express
    Accenture
    Source: Indeed

Training Options

Blended Learning

₹ 19,999

  • 90 days of flexible access to online classes
  • Lifetime access to high-quality self-paced e-learning content and live class recordings
  • 24x7 learner assistance and support
  • Classes starting in Bangalore from:-
14th Mar: Weekend Class
28th Mar: Weekend Class

Corporate Training

Customized to your team's needs

  • Blended learning delivery model (self-paced eLearning and/or instructor-led options)
  • Flexible pricing options
  • Enterprise grade Learning Management System (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support

Deep Learning Course Curriculum

Eligibility

Demand for skilled deep learning engineers is booming across a wide range of industries, making this Deep Learning with Keras and TensorFlow training well-suited for professionals at the intermediate to advanced level. We recommend this deep learning course particularly for Software Engineers, Data Scientists, Data Analysts and Statisticians with an interest in deep learning.

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Pre-requisites

Participants in this Deep Learning with Keras and TensorFlow course should have familiarity with programming fundamentals, fair understanding of basics of statistics and mathematics and good understanding of machine learning concepts.

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Course Content

  • Section 1 - Deep Learning with Tensor Flow (Self Learning)

    Preview
    • Lesson 2 - Introduction to Tensorflow

      31:55Preview
      • 2.1 Learning Objectives
        07:00
      • 2.2 Introduction to TensorFlow
        07:00
      • 2.3 TensorFlow's Hello World
        03:28
      • 2.4 Tensorflow Hello World
      • 2.5 Linear Regression With Tensorflow
      • 2.6 Logistic Regression With Tensorflow
      • 2.7 Activation Functions
      • 2.8 Intro to Deep Learning
        02:39
      • 2.9 Deep Neural Networks
        11:48
    • Lesson 3 - Convolutional Networks

      21:51Preview
      • 3.1 Learning Objectives
      • 3.2 Intro to Convolutional Networks
        04:37
      • 3.3 CNN for Classifications
        04:09
      • 3.4 CNN Architecture
        13:05
      • 3.5 Understanding Convolutions
      • 3.6 CNN with MNIST Dataset
    • Lesson 4 - Recurrent Neural Network

      24:43Preview
      • 4.1 Learning Objectives
        03:06
      • 4.2 The Sequential Problem
        03:06
      • 4.3 The RNN Model
        05:28
      • 4.4 The LSTM Model
        05:25
      • 4.5 Applying RNNs to Language Modeling
        07:38
      • 4.6 LTSM Basics
      • 4.7 MNIST Data Classification With RNN/LSTM
      • 4.8 Applying RNN/LSTM to Language Modelling
      • 4.9 Applying RNN/LSTM to Character Modelling
    • Lesson 5 - Restricted Boltzmann Machines (RBM)

      14:14
      • 5.1 Learning Objectives
        04:29
      • 5.2 Intro to RBMs
        04:29
      • 5.3 Training RBMs
        05:16
      • 5.4 RBM MNIST
      • 5.5 Collaborative Filtering With RBM
    • Lesson 6 - Autoencoders

      17:20Preview
      • 6.1 Learning Objectives
        04:51
      • 6.2 Intro to Autoencoders
        04:51
      • 6.3 Applying RNNs to Language Modelling
        07:38
      • 6.4 Autoencoders
      • 6.5 DBN MNIST
    • Lesson 1 - Welcome!

      02:06
      • 1.1 Welcome!
        02:06
      • 1.2 Learning Objectives
    • Lesson 7 - Course Summary

      02:17
      • 7.1 Course Summary
        02:17
      • Unlocking IBM Certificate
  • Section 2 - Deep Learning with Keras and Tensor Flow (Live Classes)

    Preview
    • Lesson 1 - Course introduction

      • Introduction
    • Lesson 2 - AI and Deep learning introduction

      • What is AI and Deep learning
      • Brief History of AI
      • Recap: SL, UL and RL
      • Deep learning : successes last decade
      • Demo & discussion: Self driving car object detection
      • Applications of Deep learning
      • Challenges of Deep learning
      • Demo & discussion: Sentiment analysis using LSTM
      • Fullcycle of a deep learning project
      • Key Takeaways
      • Knowledge Check
    • Lesson 3 - Artificial Neural Network

      • Biological Neuron Vs Perceptron
      • Shallow neural network
      • Training a Perceptron
      • Demo code: Perceptron ( linear classification) (Assisted)
      • Backpropagation
      • Role of Activation functions & backpropagation
      • Demo code: Backpropagation (Assisted)
      • Demo code: Activation Function (Unassisted)
      • Optimization
      • Regularization
      • Dropout layer
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project (MNIST Image Classification)
    • Lesson 4 - Deep Neural Network & Tools

      • Deep Neural Network : why and applications
      • Designing a Deep neural network
      • How to choose your loss function?
      • Tools for Deep learning models
      • Keras and its Elements
      • Demo Code: Build a deep learning model using Keras (Assisted)
      • Tensorflow and Its ecosystem
      • Demo Code: Build a deep learning model using Tensorflow (Assisted)
      • TFlearn
      • Pytorch and its elements
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Build a deep learning model using Pytorch with Cifar10 dataset
    • Lesson 5 - Deep Neural Net optimization, tuning, interpretability

      • Optimization algorithms
      • SGD, Momentum, NAG, Adagrad, Adadelta , RMSprop, Adam
      • Batch normalization
      • Demo Code: Batch Normalization (Assisted)
      • Exploding and vanishing gradients
      • Hyperparameter tuning
      • Interpretability
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Hyperparameter Tunning With Keras Tuner
    • Lesson 6 - Convolutional Neural Network

      • Success and history
      • CNN Network design and architecture
      • Demo code: CNN Image Classification (Assisted)
      • Deep convolutional models
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Image Classification
    • Lesson 7 - Recurrent Neural Networks

      • Sequence data
      • Sense of time
      • RNN introduction
      • LSTM ( retail sales dataset kaggle)
      • Demo code: Stock Price Prediction with LSTM (Assisted)
      • Demo code: Multiclass Classification using LSTM (Unassisted)
      • Demo code: Sentiment Analysis using LSTM (Assisted)
      • GRUs
      • LSTM Vs GRUs
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Stock Price Forecasting
    • Lesson 8 - Autoencoders

      • Introduction to Autoencoders
      • Applications of Autoencoders
      • Autoencoder for anomaly detection
      • Demo code: Autoencoder model for MNIST data (Assisted)
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Anomaly detection with Keras
  • Section 3 - Practice Projects

    Preview
    • Practice Projects

      • PUBG Players Finishing Placement Prediction
  • Free Course
  • Math Refresher

    Preview
    • Math Refresher

      30:36Preview
      • Math Refresher
        30:36
  • Free Course
  • Deep Learning Fundamentals

    Preview
    • Lesson 1 - Learning Objectives

      • Learning Objectives
    • Lesson 2 - Introduction to Deep Learning

      22:31Preview
      • 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

      22:56Preview
      • 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

      25:37Preview
      • 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

Project

  • Project 1

    PUBG Players Finishing Placement Prediction

    Create a model that predicts players’ finishing placement based on their final stats, on a scale of 1 (first place) to 0 (last place).

  • Project 2

    Lending Club Loan Data Analysis

    Create a model that predicts whether a loan will go into default using the historical data.

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Deep Learning Exam & Certification

Deep Learning Certificate
  • What do I need to do to unlock my Simplilearn certificate?

    Candidates need to attend one complete batch of the Online Classroom training and submit any one of the projects for assessment. After the successful assessment, the candidates are awarded the Deep Learning with TensorFlow Certification.  

  • Who provides the certification?

     

    Simplilearn provides the course completion certificate to the candidates who finish the Deep Learning online training course satisfactorily.

  • Is this course accredited?

    No, this Deep Learning course is not officially accredited.

  • How many questions are there on the Deep Learning exam?

    The Deep Learning simulation test includes a total of 144 questions.

  • How long does it take to complete this Deep Learning course?

    The Deep Learning online certification course can be finished in 45-50 hours if the course path is followed smoothly.

  • How many attempts do I have to pass the Deep Learning exam?

     

    The candidates are allowed a maximum of three attempts to clear the Deep Learning certification exam. The trainers at Simplilearn, however, assist the candidates to clear the exam successfully.

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

    To attend the Deep Learning training program, candidates need to have a system with 8 core processor and RAM of 32 GB.

  • How long is the Deep Learning Certification from Simplilearn valid for?

     

    The Deep Learning Certification offered by Simplilearn does not need renewal. It comes with lifetime validity.

Deep Learning Course Reviews

  • 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.

  • 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.

  • 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.

Why Simplilearn

Simplilearn’s Blended Learning model brings classroom learningexperience online with its world-class LMS. It combines instructor-led training, self-paced learning and personalized mentoring to provide an immersive learning experience

  • Self-Paced Online Video

    A 360-degree learning approach that you can adapt to your learning style

  • Live Virtual Classroom

    Engage and learn more with these live and highly-interactive classes alongside your peers

  • 24/7 Teaching Assistance

    Keep engaged with integrated teaching assistance in your desktop and mobile learning

  • Online Practice Labs

    Projects provide you with sample work to show prospective employers

  • Applied Projects

    Real-world projects relevant to what you’re learning throughout the program

  • Learner Social Forums

    A support team focused on helping you succeed alongside a peer community

Tensorflow Training FAQs

  • What are the course objectives?

    The presence of Deep Learning is increasing in the technology space with its implementation in various fields like climate change solutions, driving advancements in healthcare, smartphone applications, improving agricultural yields, creating efficiencies in the power grid etc.

    Simplilearn has designed the Deep Learning course with TensorFlow, which allows candidates to learn deep learning techniques and build deep learning models using TensorFlow.

    TensorFlow is an open-source software library developed by Google used for deep neural network research and contains powerful tools to help you build and implement artificial neural networks. It helps candidates create deep learning models, manage neural networks and interpret the results.

    Moreover, engineers with enhanced deep learning skills can earn an average salary of $120,000 per year, according to payscale.com.

  • What skills you learn in Deep Learning course?

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

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

  • Who should take Tensorflow Course?

    Professionals who have an intermediate to advanced level of experience can benefit from the Deep learning with TensorFlow training in Bangalore. With Artificial Intelligence finding its applications in various fields, there is a highly growing demand for proficient deep learning engineers. This course is best suited for professionals like:

    • Statisticians with an interest in deep learning
    • Data scientists
    • Data analysts
    • Software engineers

  • What are the prerequisites for learning Deep Learning with Tensorflow?

    Participants in this Deep Learning online course should have:

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

  • Who are the instructors and how are they selected?

     

    Simplilearn prefers trainers with high alumni rating only. We make sure that the trainers selected by us have a teaching experience of 12+ years along with thorough domain knowledge. The selection process involves profile screening, technical assessment, and a training demonstration prior to getting a chance to become our mentors.

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

     

    After deducing the administration fee, the remaining course fee will be refunded on canceling the enrollment. Please go through our Refund Policy to find out more.

  • How do I enroll for the online training?

     

    Candidates can enroll in the Deep Learning with TensorFlow training in Bangalore in just a few clicks. Simplilearn provides a simple process of completing the payment via:

    • Paypal
    • American Express
    • MasterCard
    • Diner’s Club
    • Visa Credit or Debit card

    A receipt will be automatically generated after the payment is successful.

  • What is Global Teaching Assistance?

     

    The faculty at Simplilearn enrich the learning experience of the students through interactive sessions and making sure that students have a strong grasp of the subject being taught. Teaching assistance is provided during business hours by our faculty who support the candidates right from class onboarding to project completion and job assistance.

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

    Candidates get a benefit of 24/7 support through calls, chat, or email. There is a community forum of our website where candidates can discuss their difficulties with the course. The community forum comes with lifelong access.

  • How can I learn more about this training program?

     

    Our support team can be contacted quickly by following some simple steps. Candidates just need to fill the Contact Us form or use the Live Chat link.

  • I am not able to access the online course. Who can help me?

     

    Simplilearn provides the Contact Us form and the Live Chat option on the website which can be used to get any kind of assistance regarding the course.

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

     

    Yes, there is the option of money-back guarantee for many of Simplilearn’s training programs. The Help and Support portal is helpful for the candidates to generate the refund requests after going through the Refund Policy.

  • What is Online Classroom training?

     

    Simplilearn provides instructor-led training sessions which are conducted via live online streaming. The candidates can join the discussion with the trainer as well as the global audience present during the class.

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

    Simplilearn provides two modes of learning. For self-paced e-learning, the candidates are provided with pre-recorded videos. With Flexi Pass learning, the candidates have the benefit of live online training as well as pre-recorded videos.

  • Are the training and course materials effective in preparing me for the Deep Learning exam?

    Yes, the training program offered by Simplilearn is aligned with the Deep Learning certification exam and ensures that the candidates pass it in their first attempt.

  • What if I miss a session?

     

    Candidates can access the recordings of each class that are provided by Simplilearn for future reference.

  • 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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