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AI & Deep Learning with TensorFlow ( L041 )

4.5 + (25,859) Students Ratings

IQ Training’s AI & Deep Learning with Tensorflow course will provide you with in-depth knowledge of deep learning libraries, Machine learning Paradigms, Neural Network Architecture. This course empowers you to master various concepts like vectorization, binary classification, artificial neural networks, and logistic regression. Our Industry experts designed in such a way that learners will easily understand and implement the concepts of deep learning, execute algorithms of deep learning, computational Graphs unfolding, Boltzmann Machines and Deep Belief Networks.

Course Price :

₹20,695
₹22,994
10%
off
Available

Live Instructor

Self Paced

Think Bigger Advantage

Live Online Classes

All our Classes are Live Instrucotor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schdules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of Completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Training Scheule
Batch Start Date Days of Training Weekday/ Weekend Timings
28-Mar-2020 Available SAT & SUN (6 WEEKS) Weekend Batch 11:00 AM - 02:00 PM (EST)
 
 
 
 
 

Course Curriculum

Learning Objectives: In this module, you will learn about the introduction of Data learning. You will also understand the basic fundamentals of Machine Learning and relevant topics of Linear Algebra and Statistics.

 

Topics:

  • Deep Learning: A revolution in Artificial Intelligence
  • Limitations of Machine Learning
  • What is Deep Learning?
  • Advantage of Deep Learning over Machine learning
  • 3 Reasons to go for Deep Learning
  • Real-Life use cases of Deep Learning
  • Review of Machine Learning: Regression, Clustering, Classification, Underfitting Optimization, Overfitting Optimization, and Reinforcement Learning

 

Hands-On

  • Implementation of Linear Regression model for predicting house prices from Boston dataset
  • Implementation of Logistic Regression model for classifying Customers based on an Automobile purchase dataset

Learning Objectives: In this module, you will learn the introduction of Neural Networks and understand it’s working i.e. how it is trained, what are the different parameters considered for its training and the activation functions that are implemented.

Topics:

  • How Deep Learning Works?
  • Activation Functions
  • Illustrate Perceptron
  • Training a Perceptron
  • Important Parameters of Perceptron
  • What is TensorFlow?
  • TensorFlow code-basics
  • Graph Visualization
  • Constants, Placeholders, Variables
  • Creating a Model
  • Step by Step - Use-Case Implementation

 

Hands-On

Building a single perceptron for categorizing on SONAR dataset

Learning Objectives: In this module, you’ll understand the backpropagation algorithm which is used for training Deep Networks. You will get to know how Deep Learning uses neural networks and backpropagation to solve the problems that Machine Learning cannot solve.

Topics:

  • Understand the limitations of a Single Perceptron
  • Understand Neural Networks in Detail
  • Illustrate Multi-Layer Perceptron
  • Backpropagation – Learning Algorithm
  • Understand Backpropagation – Using Neural Network Example
  • MLP Digit-Classifier using TensorFlow
  • TensorBoard

  Hands-On

  • Building a multi-layered perceptron for classifying Hand-written digits

Learning Objectives: In this module, you will learn about the TensorFlow framework. You will understand how TensorFlow works, its various data types & functionalities. In addition to this, you will create an image classification model.
 

Topics:

  • Why Deep Networks
  • Why do Deep Networks give better accuracy?
  • Use-Case Implementation on SONAR dataset
  • Understand How Deep Network Works?
  • How Backpropagation Works?
  • Illustrate Forward pass, Backward pass
  • Different variants of Gradient Descent
  • Types of Deep Networks

Hands-On

  • Building a multi-layered perceptron for classifying SONAR dataset

Learning Objectives: In this module, you’ll understand convolutional neural networks and their applications. You will learn the working of CNN, and also learn how to create a CNN model to solve a problem.

Topics:

  • Introduction to CNNs
  • CNN's Application
  • The architecture of a CNN
  • Convolution and Pooling layers in a CNN
  • Understanding and Visualizing a CNN

  Hands-On

  • Building a recurrent neural network for image classification.

Learning Objectives: In this module, you will learn Recurrent Neural Networks and its applications. You will understand the working nature of RNN, how LSTM is used in RNN, what is Recursive Neural Tensor Network Theory, and further you will learn how to create a Recurrent Neural Network model.

Topics:

  • Introduction to RNN Model
  • Application use cases of RNN
  • Modeling sequences
  • Training RNNs with Backpropagation
  • Long Short-Term Memory (LSTM)
  • Recursive Neural Tensor Network Theory
  • Recurrent Neural Network Model

Hands-On

 
Building a recurrent neural network for SPAM prediction.

Learning Objectives: In this module, you’ll understand Restricted Boltzmann Machine & Autoencoders along with their applications. You will understand the working nature of RBM & Autoencoders, illustrate Collaborative Filtering using RBM and understand what Deep Belief Networks.


Topics:

  • Restricted Boltzmann Machine
  • Applications of RBM
  • Collaborative Filtering with RBM
  • Introduction to Autoencoders
  • Autoencoders applications
  • Understanding Autoencoders

Hands-On

Building an Autoencoder model for classifying handwritten images which are extracted from the MNIST Dataset

Learning Objectives: In this module, you will understand how to use Keras API for implementation of Neural Networks. The main goal is to understand different functions and features that Keras provides to make the neural network implementation task very easily

Topics:


  • Define Keras
  • How to compose Models in Keras
  • Sequential Composition
  • Functional Composition
  • Predefined Neural Network Layers
  • What is Batch Normalization
  • Saving and Loading a model with Keras
  • Customizing the Training Process
  • Using TensorBoard with Keras
  • Use-Case Implementation with Keras

Hands-On

To do sentiment analysis on Twitter data reactions on GOP debate in Ohio, we build a model using Keras

  • Learning Objectives: In this module, you will learn how to use TFLearn API for implementing Neural Networks. The goal is to understand various functions and features that TFLearn provides to make the neural network implementation task very easily.


Topics:

  • Define TFLearn
  • Composing Models in TFLearn
  • Sequential Composition
  • Functional Composition
  • Predefined Neural Network Layers
  • What is Batch Normalization
  • Saving and Loading a model with TFLearn
  • Customizing the Training Process
  • Using TensorBoard with TFLearn
  • Use-Case Implementation with TFLearn


Hands-On


 To do image classification on hand-written digits, we build a recurrent neural network using TFLearn

Learning Objectives: In this module, you will learn how to approach and implement a project end to end. In addition, you will be having a QA and doubt clarification sessions.

Topics:

  • How to approach a project? 
  • Hands-On project implementation
  • What Industry expects?
  • Industry insights for the Machine Learning domain
  • QA and Doubt Clearing Session
Like the course? Enroll Now

Structure your learning and get a certificate to prove it.

Course Details

Deep Learning in TensorFlow with Python Training is crafted by industry experts to make you a Certified Deep Learning Engineer. This course offers:

  • In-depth knowledge of Deep Neural Networks 
  • Comprehensive knowledge of various Neural Network architectures such as Recurrent Neural Network, Convolutional Neural Network, Autoencoders
  • Implementation of Collaborative Filtering with RBM
  • The exposure to real-life industry-based projects using TensorFlow library
  • Rigorous involvement of an SME throughout the AI and Deep Learning Training 

Deep Learning TensorFlow with Python Training course is for all the professionals who are very much keen and passionate to learn and make their career as a Deep Learning Engineer. 

It is best suited for individuals who are:

  • Developers aspiring to be a 'Data Scientist'
  • Managers who are leading a team of analysts
  • Business Analysts who want to learn Deep Learning (ML) Techniques
  • Information Architects who aspire to gain expertise in Predictive Analytics
  • Analysts who want to learn Data Science methodologies
  • Basic programming knowledge in Python
  • Concepts about Machine Learning

IQ Training offers you complimentary self-paced courses:

  • Statistics and Machine learning algorithms
  • Python Essentials

How will I execute the practicals?

 

By using Jupyter Notebook (which is already installed on your Cloud Lab environment) you will do your Case Studies/ Assignments. The access details will be available on your LMS. Through the browser, you will be able to access your Cloud Lab environment. For any queries, the 24*7 support team will promptly assist you.

 

What is CloudLab?

 

CloudLab is a cloud-based Jupyter Notebook that is pre-installed with TensorFlow and Python packages on the cloud-lab environment. It is offered by IQ Training as a part of Deep Learning with the TensorFlow course where you can execute all the in-class demos and work on real-life projects in a fluent manner.

 

You’ll be able to access the CloudLab through your browser which requires minimal hardware configuration. In case, you get stuck in any step, our 24x7 support team is ready to assist.

IQ Training’s TensorFlow Certification Training includes the following case studies:
Using CNN, Create an image classifier and also classify images in one of the predefined 100 classes

  • Using LSTM, create a script generator and also generate scripts for any popular novel that might interest you
  • Choose your own dataset, explore the various challenges faced in the dataset domain and with any neural network architecture try to solve one of them.

AI & Deep Learning with TensorFlow Ceritficate

AI & Deep Learning with TensorFlow Reviews

25,859

Total number of reviews

4.5

Aggregate review score

80%

Course completion rate

AI & Deep Learning with TensorFlow Features

Live Online Classes

All our Classes are Live Instructor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schedules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Course Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Like the course? Enroll Now

Structure your learning and get a certificate to prove it.

AI & Deep Learning with TensorFlow FAQs

You will never miss a class at IQ Online Training! You can choose either of the two options:

  1. View the recorded session of the class available in your LMS or
  2. You can attend the missed session in any other live batch.

After the enrolment, the LMS access will be instantly provided to you able to access for lifetime which includes complete set of previous class recordings/PPTs/PDFs/assignments. You can start learning right away.

Your access to the Support Team is for lifetime. Our team will help you in resolving queries, during and after the course.

Yes, once enrollment has done for course. Access to the course material will be available for lifetime.

You can Call our support numbers listed in site OR Email us at info@iqtrainings.com.

You can view in-depth class sample recordings before the enrollment. Experience the complete learning instead of a demo session with our expertise.

All the instructors are Industry experts with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are well trained for providing an awesome learning experience to the participants.

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