About this Course

This course is a part of the Self-Driving Car Engineer Nanodegree Program.

Use OpenCV to extract information from images. Start with basic camera physics and work your way up to sophisticated machine learning tools like support vector machines, all with the goal of learning how to understand the world around us from camera images.

Skill Level
Advanced
Included in Course
  • Rich Learning Content

  • Interactive Quizzes

  • Taught by Industry Pros

  • Real World Projects

  • Student Support Community

  • Personalized Career Support

Join the Path to Greatness

This course is part of a Nanodegree Program. It is a step towards a new career in Self-Driving Car Engineer.

Nanodegree Course

Self-Driving Car Engineer - Computer Vision

Enhance your skill set and boost your hirability through innovative, independent learning.

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What You Will Learn

Lesson 1

Advanced Lane Finding

  • Train segmentation networks, which paint each pixel of the image a different color, based on its class. Use segmented images to find free space on the road.
Lesson 1

Advanced Lane Finding

  • Train segmentation networks, which paint each pixel of the image a different color, based on its class. Use segmented images to find free space on the road.
Lesson 2

Machine Learning and Stanley

  • Learn about classification, training and testing, and run a naive Bayes classifier using Scikit Learn.
Lesson 2

Machine Learning and Stanley

  • Learn about classification, training and testing, and run a naive Bayes classifier using Scikit Learn.
Lesson 3

Support Vector Machines

  • See how support vector machines work, and code one using Scikit Learn.
Lesson 3

Support Vector Machines

  • See how support vector machines work, and code one using Scikit Learn.
Lesson 4

Decision Trees

  • Learn about decision trees, including entropy and information gain.
Lesson 4

Decision Trees

  • Learn about decision trees, including entropy and information gain.
Lesson 5

Vehicle Detection and Tracking

  • In this lesson you'll learn how to detect and track vehicles using color and gradient features and a support vector machine classifier.
Lesson 5

Vehicle Detection and Tracking

  • In this lesson you'll learn how to detect and track vehicles using color and gradient features and a support vector machine classifier.

Prerequisites and Requirements

Python

See the Technology Requirements for using Udacity.

Why Take This Course

By the end of this course, you will be able to use OpenCV for an array of computer vision tasks, including camera calibration and undistortion, color space transforms and thresholding, and edge detection. You will also be able to use machine learning tools like support vector machines to identify and track vehicles.

What do I get?
  • Instructor videos
  • Learn by doing exercises
  • Taught by industry professionals
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