Course Outline

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

Requirements

  • Python programming experience.

Audience

  • Developers
  21 Hours
 

Number of participants


Starts

Ends


Dates are subject to availability and take place between 9:30 am and 4:30 pm.
Open Training Courses require 5+ participants.

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