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.

• Introduction
• 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
• Troubleshooting
• Summary and Conclusion

Contact us

email - [email protected]