Deep Learning for Self Driving Cars Training Course


Deep learning is a subfield of machine learning. It uses methods based on learning data representations and structures such as neural networks.

Keras is a high-level neural networks API for fast development and experimentation. It runs on top of TensorFlow, CNTK, or Theano.

This instructor-led, live training (online or onsite) is aimed at developers who wish to build a self-driving car (autonomous vehicle) using deep learning techniques.

By the end of this training, participants will be able to:

  • Use Keras to build and train a convolutional neural network.
  • Use computer vision techniques to identify lanes in an autonomos driving project.
  • Train a deep learning model to differentiate traffic signs.
  • Simulate a fully autonomous car.

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.


  • Python programming experience.


  • Developers

Course Outline


Setting up the Development Environment

Creating a Project

Configuring the Simulator

Preparing the Data Sets

Overview of Python Deep Learning Libraries

Applying Computer Vision Techniques to Track Lanes

Training Perceptron-Based Neural Networks to Detect Other Vehicles

Implementing Convolutional Neural Networks to Predict Steering Angle and Speed

Training a Deep Learning Model to Classify Traffic Signs

Using Polynomial Regression to Improve Predictive Accuracy

Testing the Self Driving Car


Summary and Conclusion

Leave a Reply

Your email address will not be published. Required fields are marked *