Deep Learning: Recurrent Neural Networks with Python

Recurrent Neural Networks

Deep Learning: Recurrent Neural Networks with Python

RNN-Recurrent Neural Networks, Theory & Practice in Python-Learning Automatic Book Writer and Stock Price Prediction

What you’ll learn

  • The importance of Recurrent Neural Networks (RNNs) in Data Science.
  • The important concepts from the absolute beginning with a comprehensive unfolding with examples in Python.
  • The reasons to shift from classical sequence models to RNNs.
  • Practical explanation and live coding with Python.
  • An overview of concepts of Deep Learning Theory.
  • Deep details of RNNs with examples and derivations.
  • TensorFlow (Deep learning framework by Google).
  • The use and applications of state-of-the-art RNNs (with implementations in state-of-the-art framework TensorFlow) that are much more recent and advanced in terms of accuracy and efficiency.
  • Building your own applications for automatic text generation as well as for stock price prediction.
  • And much more…


  • No prior knowledge is needed. We will start from the basics and gradually build your knowledge in the subject.
  • A willingness to learn and practice.
  • Knowledge of Python will be a plus.


Recurrent Neural Networks (RNNs), a class of neural networks, are essential in processing sequences such as sensor measurements, daily stock prices, etc. In fact, most of the sequence modelling problems on images and videos are still hard to solve without Recurrent Neural Networks. Further, RNNs are also considered to be the general form of deep learning architecture. Hence, the understanding of RNNs is crucial in all the fields of Data Science. This course addresses all these concerns and empowers you to take your career to the next level with a masterful grip on the theoretical concepts and practical implementations of RNNs in Data Science.

Why Should You Enroll in This Course?

The course ‘Recurrent Neural Networks, Theory and Practice in Python’ is crafted to help you understand not only how to build RNNs but also how to train them. This straightforward learning by doing a course will help you in mastering the concepts and methodology with regards to Python.

The two mini-projects Automatic Book Writer and Stock Price Prediction, are designed to improve your understanding of RNNs and add more skills to your data science toolbox. Also, this course will enable you to immediately apply the skills you acquire to your own projects.

How Is This Course Different?

This is a practical course that encourages you to explore and experience the real-world applications of RNNs. The course starts with the basics of how RNNs work and then goes far deep gradually. So, if your ambition is to become a Python developer, this course is indispensable.

You are assigned Home Work/ tasks/ activities at the end of the subtopics in each module. The reason for this is to make your learning easier and also to assess and further build your learning based on the concepts and methods you have learned previously. Most of these activities are coding based, preparing you for implementing the concepts you learn at your workplace.

Who this course is for:

  • People who want to take their data speak to the next level.
  • People who want to master RNNs with real datasets in Data Science.
  • People who want to implement RNNs in realistic projects.
  • Individuals who are passionate about numbers and programming.
  • Business Analysts.
  • Data Scientists.

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