Applied Artificial Intelligence (SS 2016)

Applied Artificial Intelligence

What happened to Artificial Intelligence (AI)? In the 1970s, researchers expected machines to be more intelligent than humans soon, thus, revolutionizing society and civilization. Only a few years later they had to admit that, for a computer, it is harder to reason like a five-year-old than to play a game of chess. The AI hype burst.

And today? 

Unnoticed (and often not under the keyword "AI"), AI applications have become ubiquitous in our everyday lifes:

  • Speech control in cars, mobile phones, etc.
  • Face recognition in cameras
  • (Learning) Spam classification in e-mail clients
  • AI in computer games
  • Semantic search of the Internet
  • Machine translation services in the Internet
  • Not to speak of numerous professional AI applications as business intelligence, robotics, etc.

 

So, AI applications are relevant - reason enough to offer a course on AI.

AI courses have a long history in Computer Science departments. Many of those courses focus on the theory behind AI. This course "Applied AI" has a different focus: the architecture and development of AI applications with state-of-the-art technology, languages, and tools.

Also see the module description

 

Lectures

Lectures and lab sessions will be interwoven. The lecture is structured as follows (current lecture slides for download):

  1. Introduction
  2. Knowledge Representation
  3. Queries
  4. AI Application Architecture
  5. Information Retrieval
  6. Natural Language Processing
  7. Machine Learning
  8. Computer Vision
  9. Agents
  10. Questions & Answers

 

Lectures will be video recorded. Download link : https://lernen.h-da.de/course/view.php?id=5046 . Enrolment key: apartinss2016 . Login via h_da user id an password.

 

Laboratory

In this course, you will as teams implement an AI application for a digital museum.  Thereby, you will research and practice all methods and technology necessary.

The lab sessions are interlaced with the lecture (Mo., 12:00 ‚Äď 17:30 each week)

Please, bring your own notebook if you own one. You need h_da WiFi access.

Assignments:

  1. Introduction
  2. Knowledge Representation
  3. Queries
  4. AI Application Architecture
  5. Information Retrieval
  6. Natural Language Processing
  7. Machine Learning
  8. Computer Vision
  9. Questions & Answers

 

Material

 

Examination

There will be oral examinations on July 7 and 13 in my office D15/3.05. Exam Schedule