TensorFlow - An open source Machine Learning Course

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About TensorFlow - An open source Machine Learning Course

TensorFlow is a through and through open source arrange for AI. It has a sweeping, versatile condition of gadgets, libraries, and system resources that lets researchers push the front line in ML and fashioners adequately develop and pass on ML-energized applications. TensorFlow was at first made by experts and originators working on the Google Brain bunch inside Google's Machine Intelligence Research relationship to lead AI and significant neural frameworks explore. The system is adequately broad to be material in a wide collection of various spaces, as well.

TensorFlow gives stable Python and C++ APIs, similarly as non-guaranteed backward ideal API for various tongues.

TensorFlow - An open source Machine Learning Course Overview

This is an Artificial Intelligence training program that is a comprehensive learning approach for mastering the domains of Artificial Intelligence, Data Science, Business Analytics, Business Intelligence, Python coding and Deep Learning. This training program enables you to take on challenging roles in the Artificial Intelligence domain.

The AI courses will make students industry-ready for Artificial Intelligence and Data Science job roles.Upon completion of this AI Engineer Program, you will receive the certificate from our side in the Artificial Intelligence courses on the learning path*. This certificate will testify to your skills as an expert in Artificial Intelligence.

Instructor-led, Live & Interactive Sessions

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How we prepare you

Artificial Intelligence

Upon completion of this program you will get 360-degree understanding of Machine Learning. This course will give you thorough learning experience in terms of understanding the concepts, mastering them thoroughly and applying them in real work environment.

Hands-on experience in a live project

You will be given industry level real time projects to work on and it will help you to differentiate yourself with multi-platform fluency, and have real-world experience with the most important tools and platforms.

Unlimited Mock Interview and Quiz Session

As part of this, You would be given complete interview preparations kit, set to be ready for the Machine Learning. This kit has been crafted by 200+ years industry experience and the experiences of nearly 10000 DevOpsSchool's Machine Learning learners worldwide.

Agenda of the TensorFlow - An open source Machine Learning Course Download Curriculum

  • Introduction of Artificial Intelligence
  • Data Science & Python
  • Machine Learning
  • Deep Learning
  • Natural Language processing(NLP)
  • Decoding Artificial Intelligence
  • Fundamentals of Machine Learning and Deep Learning
  • Machine Learning Workflow
  • Performance Metrics

  • Introduction to TensorFlow
  • Architecture of Tensorflow
  • Installation on Local Machine
  • Using TensorFlow in Google Colab
  • Working with Tensors and Operations
  • Keras Low level api
  • Labs:-
  • 1. Installing tensorflow on local machine 2. Working with google colab
  • a. From Biological to Artificial Neurons
  • b. Different activation functions
  • c. What is perceptron?
  • d. Multilayer perceptron and back propagation
  • e. Working with sequential api
  • f. Working with the functional api
  • g. Using callbacks
  • h. Tensorboard for visualization
  • i. Labs:-
  • 1. Classification on iris dataset using perceptron model
  • 2. Image classification on fashion MNIST dataset using sequential and functional API
  • 3. Improving the model using callbacks
  • a. Challenges of Deep Neural Networks’
  • b. Vanishing and Exploding gradients
  • c. Glorot and He Initialization
  • d. Non Saturating Activation Functions
  • e. Different activation functions effect on deep neural nets
  • f. Batch normalization
  • g. Reusing the pre-trained layers in Neural nets
  • h. Faster optimizers
  • i. L1 and L2 regularization
  • j. Dropouts and their purposes
  • k. Labs:- 1. Classification of MNIST dataset and performance of models by the use of
  • different activation functions.
  • 2. Classification by using a pre-trained layer of model to reduce the computation time.
  • 3. Reducing the overfitting through the use of regularization in various models.
  • a. The data api
  • b. Chaining transformations
  • c. Pre-processing the data
  • d. TFR record format and compressed files
  • e. Introduction to protocol buffer
  • f. Processing the Input features
  • g. TF transform
  • h. Tensorflow datasets project
  • i. Labs:- 1. Implementation of basic functions like repeat, batch, shuffle required for
  • preprocessing.
  • 2. Implement interleave() so as to read many files at a time using tensorflow for improving
  • the performance.
  • 3. Storing and accessing the files stored in tfrecord format for better processing.
  • a. Inspiration to the CNN
  • b. Architecture of CNN
  • c. Convolution layers in CNN
  • d. Filters in CNN
  • e. Pooling layer in CNN
  • f. Depth pooling in CNN
  • g. Different architectures of CNN
  • h. Labs:- 1. Implementing different filters to find the different patterns from the image.
  • 2. Progressively reduce the spatial size of an image.
  • 3. Classifying the fashion MNIST dataset by using CNN.
  • a. Single neuron RNN
  • b. Working with RNN neural network
  • c. Input and Output Sequences in RNN
  • d. Introduction to Deep RNN
  • e. Forecasting using RNN
  • f. Unstable gradient problem
  • g. Architecture of LSTM
  • h. Architecture of GRU
  • i. Labs:- 1. Forecasting using simple RNN, Deep RNN, LSTM and GRU
  • a. Introduction to Natural Language processing
  • b. Shakespear text generation using char RNN
  • c. Stateless and stateful RNN
  • d. Concept of sentiment analysis
  • e. Encoder and Decoder Network for Neural Machine Translation
  • f. Pre-processing required for encoder and decoder
  • g. Concept of Beam Search
  • h. Overview of attention mechanism
  • i. Labs:- 1. Generating Shakespearean text using character RNN, Bidirectional RNN.
  • 2. Sentiment analysis of IMDB dataset.
  • a. Introduction to Autoencoders and GAN
  • b. Efficient data representation
  • c. Dimensionality reduction using autoencoders
  • d. Introduction to stacked autoencoders
  • e. Training one autoencoder at a time
  • f. Recurrent autoencoders
  • g. Sparse autoencoders
  • h. Generative adversarial networks
  • i. Deep Convolutional GANs
  • j. Labs:- 1. Autoencoder for the dimensionality reduction
  • 2. Reconstruction of images using recurrent auto encoder
  • a. Introduction to reinforcement learning
  • b. Learning to optimize rewards
  • c. Policy Search
  • d. Introduction to OpenAI Gym
  • e. Neural Network Policies
  • f. Credit Assignment Problem
  • g. Markov Decision Process
  • h. Q Learning
  • i. Deep Q Learning
  • j. Labs:- 1. Train a Deep Q network with TF agent(Cartpole Environment)
Understanding the problems
Concept Discussion
Lab & Exercise
Assessments & Projects


In Artificial Intelligence Course a Participant will get total 5 real time scenario based projects to work on, as part of these projects, we would help our participant to have first hand experience of real time scenario based software project development planning, coding, deployment, setup and monitoring in production from scratch to end. We would also help our participants to visualize a real development environment, testing environment and production environments.


1 Course for Artificial Intelligence
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Lifetime Technical Support
Lifetime LMS access
Top 46 Tools
Interview Kit
Training Notes
Step by Step Web Based Tutorials
Training Slides

With the demand for AI in a broad range of industries, Our AI course is well suited for a variety of roles and disciplines, including:

  • Developers who are aspiring to be an Artificial Intelligence Engineer or Machine Learning Engineer
  • Analytics Managers who are leading a team of analysts
  • Information Architects who want to gain expertise in Artificial Intelligence algorithms
  • Analytics professionals who want to work in machine learning or artificial intelligence
  • Freshers and Graduates looking to build a career in Artificial Intelligence and machine learning
  • Professionals who would like to tackle Artificial Intelligence in their fields to get more insight

Participants in this course should have:

  • Understanding of the fundamentals of Python programming
  • Basic knowledge of statistics

You will have the skills required to help you to land a dream job. Jobs that are ideal for Artificial Intelligence trained professionals include:

  • Artificial Intelligence Engineer
  • Data Scientist
  • Analytics Manager/Lead
  • Machine Learning Engineer
  • Statistical Programming Specialist

TensorFlow - An open source Machine Learning Course framework for everyone CERTIFICATION

What are the benefits of "Artificial Intelligence" Certification?

During this program, you will be engaged in various projects and assignments, which include real-world industry scenarios. Which will be very helpful to you and you can expedite your career effortlessly.You would be glad to know that our certification training is recognized all around the world.

TensorFlow - An open source Machine Learning Course FAQs

Because We provide the best Artificial Intelligence training course that gives you all the skills needed to work in the domains of AI, Machine Learning, Deep Learning, Data Science with R Statistical computing and Python to give the professionals an added advantage. After the completion of the training, you will be awarded the Artificial Intelligence certification.

You can know more about us on Web, Twitter, Facebook and linkedin and make your own decision. Also, you can email us to know more about us. We will call you back and help you more about the trusting DevOpsSchool for your online training.

You will have the skills required to help you to land a dream job. Jobs that are ideal for Artificial Intelligence trained professionals are like Artificial Intelligence Engineer, Analytics Manager/Lead, Machine Learning Engineer, Statistical Programming Specialist.

All of our trainers are industry experts with years of relevant experience in the industry. All of them have gone through a scrupulous 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.

We provide the best Artificial Intelligence training course that gives you all the skills needed to work in the domains of AI, Machine Learning, Deep Learning, Data Science with R Statistical computing and Python to give the professionals an added advantage. After the completion of the training, you will be awarded the Artificial Intelligence certification.

You will be working on real-time projects and step-by-step assignments which have high relevance in the corporate world, and the curriculum is designed by industry experts. Upon the completion of the training course, you can apply for some of the best dream jobs in top MNCs around the world and can get top salaries. We offer lifetime access to videos, course materials, at no extra fee. Hence, it is clearly a one-time investment.

You will never lose any lecture at DevOpsSchool. There are two options available: You can view the class presentation, notes and class recordings that are available for online viewing 24x7 through our Learning management system (LMS). You can attend the missed session, in any other live batch or in the next batch within 3 months. Please note that, access to the learning materials (including class recordings, presentations, notes, step-bystep-guide etc.)will be available to our participants for lifetime.

Please email to contact@DevopsSchool.com

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If you are reaching to us that means you have a genuine need of this training, but if you feel that the training does not fit to your expectation level, You may share your feedback with trainer and try to resolve the concern. We have no refund policy once the training is confirmed.

Our fees are very competitive. Having said that if the participants are in a group then following discounts can be possible based on the discussion with representative.

  • Two to Three students – 10% Flat discount
  • Four to Six Student – 15% Flat discount
  • Seven & More – 25% Flat Discount

DevOpsSchool provides "TensorFlow - An open source Machine Learning Course" certificate accredited by DevOpsCertificaiton.co which is industry recognized and does holds high value. Participant will be awarded with the certificate on the basis of projects, assignments and evaluation test which they will get within and after the training duration.



Abhinav Gupta, Pune


The training was very useful and interactive. Rajesh helped develop the confidence of all.


Indrayani, India


Rajesh is very good trainer. Rajesh was able to resolve our queries and question effectively. We really liked the hands-on examples covered during this training program.


Ravi Daur , Noida


Good training session about basic Devops concepts. Working session were also good, howeverproper query resolution was sometimes missed, maybe due to time constraint.


Sumit Kulkarni, Software Engineer


Very well organized training, helped a lot to understand the DevOps concept and detailed related to various tools.Very helpful


Vinayakumar, Project Manager, Bangalore


Thanks Rajesh, Training was good, Appreciate the knowledge you poses and displayed in the training.


Abhinav Gupta, Pune


The training with DevOpsSchool was a good experience. Rajesh was very helping and clear with concepts. The only suggestion is to improve the course content.

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  DevOpsSchool is offering its industry recognized training and certifications programs for the professionals who are seeking to get certified for DevOps Certification, DevSecOps Certification, & SRE Certification. All these certification programs are designed for pursuing a higher quality education in the software domain and a job related to their field of study in information technology and security.

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