About this Course

Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. In this course, you’ll learn the basics of modern AI as well as some of the representative applications of AI. Along the way, we also hope to excite you about the numerous applications and huge possibilities in the field of AI, which continues to expand human capability beyond our imagination.

Note: Parts of this course are featured in the Machine Learning Engineer Nanodegree and the Data Analyst Nanodegree programs. If you are interested in AI, be sure to check out those programs as well!

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Intro to Artificial Intelligence
Course Cost
Free
Timeline
Approx. 4 months
Skill Level
Intermediate
Included in Course
  • Icon course 01 3edf6b45629a2e8f1b490e1fb1516899e98b3b30db721466e83b1a1c16e237b1 Rich Learning Content

  • Icon course 04 2edd94a12ef9e5f0ebe04f6c9f6ae2c89e5efba5fd0b703c60f65837f8b54430 Interactive Quizzes

  • Icon course 02 2d90171a3a467a7d4613c7c615f15093d7402c66f2cf9a5ab4bcf11a4958aa33 Taught by Industry Pros

  • Icon course 05 237542f88ede3178ac4845d4bebf431ddd36d9c3c35aedfbd92e148c1c7361c6 Self-Paced Learning

  • Icon course 03 142f0532acf4fa030d680f5cb3babed8007e9ac853d0a3bf731fa30a7869db3a Student Support Community

Join the Path to Greatness

This free course is your first step towards a new career with the Machine Learning Engineer Nanodegree Program.

Free Course

Intro to Artificial Intelligence

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

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Course Leads

  • Peter Norvig
    Peter Norvig

    Instructor

  • Sebastian Thrun
    Sebastian Thrun

    Instructor

What You Will Learn

Lesson 1

Fundamentals of AI

  • Statistics, Uncertainty, and Bayes networks.
  • Machine learning.
  • Logic and planning.
Lesson 1

Fundamentals of AI

  • Statistics, Uncertainty, and Bayes networks.
  • Machine learning.
  • Logic and planning.
Lesson 2

Applications of AI

  • Image processing and computer vision.
  • Robotics and robot motion planning.
  • Natural language processing and information retrieval.
Lesson 2

Applications of AI

  • Image processing and computer vision.
  • Robotics and robot motion planning.
  • Natural language processing and information retrieval.

Prerequisites and Requirements

Some of the topics in Introduction to Artificial Intelligence will build on probability theory and linear algebra. You should have understanding of probability theory comparable to that covered in our Intro to Statistics course.

See the Technology Requirements for using Udacity.

Why Take This Course

Artificial Intelligence (AI) technology is increasingly prevalent in our everyday lives. It has uses in a variety of industries from gaming, journalism/media, to finance, as well as in the state-of-the-art research fields from robotics, medical diagnosis, and quantum science. In this course you’ll learn the basics and applications of AI, including: machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.

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