Deep Learning with TensorFlow 2.0 Certification Training in Cedar Rapids, IA

  8915 ratings     19587 students
    • Learn and get certified in Deep Learning with TensorFlow 2.0 from the comfort of your home and transform your career

    • Curated by industry experts, the course will help you master popular algorithms like CNN, RCNN, RNN, LSTM, RBM using the latest TensorFlow 2.0 package in Python

    • 30 hours of Instructor-led Deep Learning with TensorFlow 2.0 Certification Classes with Hands-on practice with Google Colab notebook

    • We guarantee great value at the lowest price in the industry

    • Exclusive Buy 1 - Get 1 Free Offer (till 31st July, 2021) Know More

Online Self-Learning
  • Anytime, Anywhere: Learn whenever it is convenient to you
  • Learn through high quality presentations, quizzes, recordings of live classes; installation guide available in LMS
  • Course content created using real life case studies and live project
  • 24x7 customer support through email and ticket-based
  • Lifetime access to online Learning Management System (LMS)
USD 299 179
Live-Virtual Class
  • Attend Deep Learning with TensorFlow 2.0 course from the comfort of your home with a computer
  • 30 Hours of Live Classes taught by experts over online training platform
  • Classes are taught in 10 sessions of 3 hours each or 15 sessions of 2 hours each
  • Taught using real life case studies and practicals are performed using Google Colab notebook
  • Lifetime access to Learning Management System (LMS) where presentations & class recordings are available
  • In case you miss a session, you can either attend the missed session in any other live batch or view the recorded session in the LMS
  • Deep Learning Engineer certification based on the project completed during the training
  • Access to community forums for peer interaction and knowledge sharing
  • 24x7 support for lifetime through ticket based support system
  • Exclusive Buy 1 - Get 1 Free Offer (till 31st Mar, 2021) Know More
Date : Aug 20 Sep 18 (Custom)
Time : 08:30 PM to 11:30 PM (CDT)
USD 599 369

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Date : Sep 18 Oct 17 (Weekend)
Time : 10:00 AM to 01:00 PM (CDT)
USD 599 369
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Deep Learning with TensorFlow 2.0 Overview

Encertify's Deep Learning with TensorFlow 2.0 course will help you master popular algorithms like CNN, RCNN, RNN, LSTM, RBM using the latest TensorFlow 2.0 package in Python. You will be also be offered the opportunity to work on various real-time projects like Emotion and Gender Detection, Auto Image Captioning using CNN and LSTM, and many more.

After completing this course, you should be able to:

  • Get yourself introduced and trained with TensorFlow 2.0.
  • Understand the concept of Single-Layer and Multi-Layer Perceptron by implementing them in Tensorflow 2.0
  • Learn about the working of CNN algorithm and classify the image using the trained model
  • Grasp the concepts on important topics like Transfer Learning, RCNN, Fast RCNN, RoI Pooling, Faster RCNN, and Mask RCNN
  • Understand the concept of Boltzmann machine and Auto Encoders
  • Implement Generative Adversarial Network in TensorFlow 2.0
  • Work on the Emotion and Gender Detection project and strengthen your skill on OpenCV and CNN
  • Understand the concept of RNN, GRU, and LSTM
  • Perform Auto-Image Captioning using CNN and LSTM

  Buy 1 - Get 1 Free


Deep Learning with TensorFlow 2.0 Course Topics

  • What is Deep Learning?
  • Curse of Dimensionality
  • Machine Learning vs. Deep Learning
  • Use cases of Deep Learning
  • Human Brain vs. Neural Network
  • What is Perceptron?
  • Learning Rate
  • Epoch
  • Batch Size
  • Activation Function
  • Single Layer Perceptron
  • Introduction to TensorFlow 2.x
  • Installing TensorFlow 2.x
  • Defining Sequence model layers
  • Activation Function
  • Layer Types
  • Model Compilation
  • Model Optimizer
  • Model Loss Function
  • Model Training
  • Digit Classification using Simple Neural Network in TensorFlow 2.x
  • Improving the model
  • Adding Hidden Layer
  • Adding Dropout
  • Using Adam Optimizer
  • Image Classification Example
  • What is Convolution
  • Convolutional Layer Network
  • Convolutional Layer
  • Filtering
  • ReLU Layer
  • Pooling
  • Data Flattening
  • Fully Connected Layer
  • Predicting a cat or a dog
  • Saving and Loading a Model
  • Face Detection using OpenCV
  • Regional-CNN
  • Selective Search Algorithm
  • Bounding Box Regression
  • SVM in RCNN
  • Pre-trained Model
  • Model Accuracy
  • Model Inference Time
  • Model Size Comparison
  • Transfer Learning
  • Object Detection – Evaluation
  • mAP
  • IoU
  • RCNN – Speed Bottleneck
  • Fast R-CNN
  • RoI Pooling
  • Fast R-CNN – Speed Bottleneck
  • Faster R-CNN
  • Feature Pyramid Network (FPN)
  • Regional Proposal Network (RPN)
  • Mask R-CNN
  • What is Boltzmann Machine (BM)?
  • Identify the issues with BM
  • Why did RBM come into the picture?
  • Step by step implementation of RBM
  • Distribution of Boltzmann Machine
  • Understanding Autoencoders
  • Architecture of Autoencoders
  • Brief on types of Autoencoders
  • Applications of Autoencoders
  • Which Face is Fake?
  • Understanding GAN
  • What is Generative Adversarial Network?
  • How does GAN work?
  • Step by step Generative Adversarial Network implementation
  • Types of GAN
  • Recent Advances: GAN
  • Where do we use Emotion and Gender Detection?
  • How does it work?
  • Emotion Detection architecture
  • Face/Emotion detection using Haar Cascade
  • Implementation on Colab
  • Issues with Feed Forward Network
  • Recurrent Neural Network (RNN)
  • Architecture of RNN
  • Calculation in RNN
  • Backpropagation and Loss calculation
  • Applications of RNN
  • Vanishing Gradient
  • Exploding Gradient
  • What is GRU?
  • Components of GRU
  • Update gate
  • Reset gate
  • Current memory content
  • Final memory at current time step
  • What is LSTM?
  • Structure of LSTM
  • Forget Gate
  • Input Gate
  • Output Gate
  • LSTM architecture
  • Types of Sequence-Based Model
  • Sequence Prediction
  • Sequence Classification
  • Sequence Generation
  • Types of LSTM
  • Vanilla LSTM
  • Stacked LSTM
  • Bidirectional LSTM
  • How to increase the efficiency of the model?
  • Backpropagation through time
  • Workflow of BPTT
  • Auto Image Captioning
  • COCO dataset
  • Pre-trained model
  • Inception V3 model
  • Architecture of Inception V3
  • Modify last layer of pre-trained model
  • Freeze model
  • CNN for image processing
  • LSTM or text processing

Deep Learning with TensorFlow 2.0 Certification & Exam

Towards the end of the course, you will work on a project involving Deep Learning with TensorFlow 2.0. On successful completion of the project, you will be certified as a "Deep Learning Engineer".

Deep Learning with TensorFlow 2.0 Certification Training

Why Choose Us


More than 12000 satisfied learners have taken this course on Deep Learning.

Convenient Schedule

We have batches both on weekends and weekdays to accommodate the need of different professionals.

Low Cost

Without compromising on quality, we have priced our Deep Learning with TensorFlow 2.0. certification courses very competitively. We guarantee that you will find us more economical than any other training provider.

Unmatched Quality

We along with our affiliate partners are dedicated in creating the best quality study materials and student experience across our products. All content complies with quality conformance standards to ensure that our content is the best in class and free of any errors.

Course Design

Based on years of experience in delivering effective professional training, our courses are designed not only to provide you the Deep Learning certification, but also to empower with best practices. We achieve this by providing a unique blend of concepts, case studies, and simulations that guarantee our students know how to implement Deep Learning concepts in real life.


All our trainers are highly qualified and certified in various industry frameworks. They have years of professional experience in their respective fields and they are not only experts in their domains but are also passionate about sharing their knowledge and expertise with other professionals thereby enriching careers of students.

Never miss a class

In case you miss a session because of any reason, you can either attend the missed session in any other live batch or view the recorded session in the LMS.

Lifetime Access

You get lifetime access to the Learning Management System (LMS). Class recordings and presentations can be viewed online from the LMS.

Customer Satisfaction

We are here to ensure you get heard 24/7, and to take care of every single questions and doubts you have. Our dedicated support team will provide you best in class round the clock customer support. Superior customer service is the hallmark of our company and we always go the extra mile to satisfy each of our customers whether an individual or a corporate client.

Deep Learning with TensorFlow 2.0 Frequently Asked Questions

Please click on the "ENROLL" button against the course you wish to enroll for. You need to provide your details (Name, Email ID, etc) and pay the course fee.

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Yes, we do offer additional discounts to group and corporate training customers. Please get in touch with us by email ([email protected]) to find out more about our group discount offerings.

Use the "Drop a query"section in this page or check "Contact Us" section. Alternatively, please send an email to [email protected] to find out more about our course offerings.

We strongly recommended to continue with one mode of training for better learning experience. However, in case situation demands, you can switch mode of training upon availability of respective courses with other training modes. Check with our team well in advance for any change request to avoid logistics and operational inconvenience.

If you're between jobs and have been unemployed for last the 6 months, or you're a student taking a course for career growth, we do provide additional discounts for you on selected courses. Please email [email protected] to avail this benefit and discount coupon.

Note: These discounts are available on selected courses, have a limited number and on a first-come-first-serve basis.

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Encertify Rating
4.7 out of 5 (20516 ratings)