Staffordshire University
Faculty of Computing, Engineering and Technology

New York University Skopje
Faculty of Computer Science and Information Technology

Further Artificial Intelligence

Course CE00334-3

Winter 2009



Lectures

Igor Trajkovski will be lecturing this course.

Class Hours:

E-mail address: trajkovski AT nyus DOT edu DOT mk
Phone Number: +389 2 2034 636

There will be 13 lectures, 1 revision lecture, and final exam, spread over 15 weeks.

There will be one assessed practical for the course, which will be an application of machine learning algorithms.

Module Details

Assessment Details

An EXAM length 2 HOURS weighted at 50%. An ASSIGMT weighted at 50%.

50% Assignment (learning outcomes 2, 3)
50% Examination length 2 hours (learning outcomes 1, 3)

Indicative Content

Machine Learning, Decision Trees, Neural Networks, Pattern Recognition, Natural Language Processing.

Learning Strategies

Two lectures per week.
One tutorial per week.

Resources

Python, C/C++, JAVA

Special Admissions Requirements

Prior study of AI Methods (CE00341-2) or equivalent.

Learning Outcome

  1. EXPLAIN THE OPERATION OF A RANGE OF ADVANCED ARTIFICIAL INTELLIGENCE TECHNIQUES, AND SOFTWARE. (Knowledge & Understanding)
  2. DESIGN AND IMPLEMENT A SOFTWARE ARTEFACT THAT MODELS/SIMULATES INTELLIGENT BEHAVIOUR FOR A GIVEN PROBLEM DOMAIN USING APPROPRIATE METHODS. (Enquiry)
  3. MAKE A SELECTION BETWEEN CANDIDATE TECHNIQUES BASED UPON A RATIONAL CRITICAL EVALUATION OF THE REQUIREMENTS OF A PARTICULAR PROBLEM. (Problem Solving)

Text book

Artificial Intelligence: A Modern Approach
(Second Edition) by Stuart Russell and Peter Norvig

Slides of the lectures

    Uncertain knowledge and reasoning

  1. 16.Sep Uncertainty
  2. 23.Sep Bayesian networks
  3. 30.Sep Inference in Bayesian networks

    Learning

  4. 07.Oct Learning from Observations
  5. 14.Oct Bayesian learning
  6. 21.Oct Text classification
  7. 28.Oct Neural Networks
  8. 04.Nov Instance Based Learning
  9. 11.Nov Ensembles

    Communicating, perceiving, and acting

  10. 18.Nov Machine Translation
  11. 25.Nov WEKA - Data Mining with Open Source Machine Learning Software
  12. 02.Dec Parsing natural language sentences, Consultations about Assigments

    Conclusions

  13. 09.Dec AI: Present and the Future
  14. 16.Dec Revision Week
  15. 23.Dec Final Exam

Resources

AI Magazine (old issues available on-line for free)
Python implementation of algorithms from Russell and Norvig's 'Artificial Intelligence: A Modern Approach'
Data sets from Russell and Norvig's "Artificial Intelligence: A Modern Approach"