Deep Learning for Self Driving Cars Training Course

  1. Artificial Intelligence (AI) Training
  2. Machine Learning Training
  3. Deep Learning Training
  4. Keras Training
  5. Deep Learning for Self Driving Cars Training Course

Course Code

selfdrivingcar

Duration

21 hours (usually 3 days including breaks)

Requirements

  • Python programming experience.

Audience

  • Developers

Overview

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 (onsite or remote) is aimed at developers who wish to build a self-driving car using deep learning techniques.

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

  • Use computer vision techniques to identify lanes.
  • Use Keras to build and train convolutional neural networks.
  • 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.

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

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