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Deep Learning with Tensorflow and Keras Course

Master deep learning concepts and models using Keras and TensorFlow frameworks. Learn to implement deep learning algorithms and prepare for a career as a Deep Learning Engineer.

Deep Learning with TensorFlow and Keras is an open-source end-to-end platform that includes a framework for performing various machine learning tasks, whereas Keras is a high-level neural network library that operates on top of TensorFlow. Both offer high-level APIs that make it simple to design and train models, while Keras is more approachable due to the inclusion of Python.

What will you learn in Deep Learning with TensorFlow and Keras?

  1. Introduction to Deep learning fundamentals
  2. Fundamentals of Keras and TensorFlow
  3. Keras models
  4. Keras callbacks
  5. Artificial Neural Network
  6. Convexity
  7. Gradient Descent
  8. Stachastic Gradient descent From Fully connected layer to convolution
  9. Convolution for images
  10. Padding and stride
  11. Relu
  12. Pooling
  13. Fully connected Neural network
  14. RNN Intuition
  15. Implementation of RNN
  16. Back Propagation through time
  17. Modern RNN
  18. Boltzmann Machine Intuition
  19. Implementation of Boltzmann Machine
  20. Contrastive divergence
  21. Deep Boltzmann machine
  22. Autoencoders training
  23. Type of autoencoders


Basic understanding of Python is required.


A warm welcome to Deep learning with Tensor flow and Keras training course.
Deep learning is a subfield of machine learning that is a set of algorithms inspired by the brain’s structure and function.

The Deep Learning market size is estimated to be worth $18.16 billion by the end of 2023. That means the market is growing at a rapid rate of 41 percent from 2018 to 2023. Deep learning is getting used in all sectors – healthcare, fintech, e-commerce. As per Glassdoor, the average salary of a Deep learning engineer is $136K.
TensorFlow and Keras are the two most popular frameworks used in Deep Learning.
TensorFlow is an open-source machine learning framework that Google has created. It used to design, build, and train deep learning models. It offers easy model building irrespective of the language or platform you are using.

How to create models and optimization in Keras and TensorFlow

Keras is a high-level neural networks library that runs on top of TensorFlow, CNTK, and Theano. It is easy to use and allows fast prototyping. Kera framework is python based, so it is very easy to debug. At the same time, it provides ease for extensibility.
This Deep Learning with the Tensor flow and Keras course is curated by industry AI experts and aligned with the industry’s need. You will learn how to create models and optimization in Keras and TensorFlow, solve the Convolutional Neural network (CNN) and Recurrent Neural Network (RNN), and understand the implementation of the Boltzmann Machine and Autoencoders.
This course will prepare you to gain deep learning skills using Tensorflow and Keras.

By the end of this course, you will get the necessary knowledge to enhance your career as a Deep learning engineer.
This course will help you boost your career in the booming Artificial Intelligence domain. So, start your AI journey today. We will see you on the course.

Who is this course for?

1. College Freshers
2. Anyone who is willing to learn Deep learning with Tensorflow and Keras in simple and easy steps

Course Content

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Course Includes

  • 9 Lessons
  • 111 Topics
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