Course Syllabus

Artificial Intelligence 

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Semester & Location:

Fall 2019- DIS Copenhagen

Type & Credits:

Elective Course - 3 credits

Major Disciplines:

Computer Science. Mathematics

Faculty Members:

 Lucian Leahu

Program Director:

Iben de Neergaard, 

Time & Place:

Mondays, 13.15-16.10

Location: V10-A12

Course Description

Artificial Intelligence (AI) is behind your smart phone’s intelligent personal assistant, driverless cars, robots, government fraud detection systems, and the image recognition algorithms of Facebook and Instagram, just to mention a few examples.  This course introduces you to core techniques and applications of Artificial Intelligence using primarily symbolic methods in an agent-oriented paradigm.

Classes are a mix of discussions of theory/core concepts and hands-on problem solving. The majority of the course work is carried out in groups.

During the course, you will implement simple search-based agents solving transportation tasks in a virtual environment. The virtual environment is an idealized model of systems of delivery robots in hospitals, the warehouse robots at Amazon, etc. This part of the course is referred to as the programming project.

The course consists of the following parts:

  1. Introduction to AI (Foundations of AI + Intelligent agents). 2 sessions.
  2. The philosophy, ethics and future of AI. 2 sessions + group presentations throughout the course (critical review).
  3. Problem-solving by searching: uninformed and informed search. This part covers the background material for the programming project. 4 sessions.
  4. Lab work on the programming project. 8 sessions.
  5. Machine learning: Neural networks and reinforcement learning. A short crash course in important machine learning techniques. 2 sessions.
  6. Game playing and adversarial search. This covers 4 sessions and the mandatory assignment AI in board games (described below).
  7. Lab work on AI in board games. 2 sessions. 

Course Themes

  1. Foundations of AI
  2. Intelligent agents
  3. Problem-solving by searching
  4. Adversarial search (games)
  5. Neural networks and reinforcement learning
  6. Applications of AI
  7. Philosophy, ethics, and future of AI


Learning Outcomes

Upon successfully completing this course, you will be able to:

  • Correctly determine which AI technique(s) should be used to solve a particular problem - if any
  • Design software agents that act rationally in complex domains
  • Design formal problems in AI and identify important features and properties
  • Explain concisely the scope of AI, its potential for society as well as its limitations
  • Discuss contemporary applications of AI from both a technical and an ethical perspective



One year of introduction to computer science and a semester of calculus at university level. It is strongly recommended that you have had an introduction to data structures and algorithms, mathematical modeling and imperative programming.


Lucian Leahu, PhD in Computer Science from Cornell University (2012). Assistant professor at ITU Copenhagen since 2015. ERCIM Postdoctoral Fellow at the Swedish Institute of Computer Science (2012-2013) and Project Leader in the Media Technology and Interaction Design Department at the Royal Institute of Technology (2014). With DIS since 2019.



Stuart Russell and Peter Norvig: Artificial Intelligence - A Modern Approach. 3rd ed., global edition, Pearson, 2014.

All readings in the Course Summary below refer to this textbook unless otherwise noted. 


Assignments and Evaluation

More details will be provided by your instructor in class.

  • Assignment: Programming project (40%). The project is divided into two parts, each accounting for 20% of the final grade.  
  • Assignment: AI in board games (20%).
  • Presentation: critical review of a mainstream media article on the philosophy/ethics/future of AI (15%).
  • Final exam: A final written exam with exercises similar to the ones provided during classes (25%).

The two assignments and the presentation are group work. Only the final exam is individual. 


General note regarding assignments

Papers should be correctly formatted and referenced. Double-spaced. Times New Roman. 12-point font. 1-inch margins. At DIS, one page equals 300 words. Papers not adhering to these guidelines will result in point deductions. Late assignments will be deducted a third of a grade point per day it is late. All work must be handed in in order to get a passing grade.



You are expected to attend all DIS classes when scheduled. All classes, events and field trips are mandatory unless marked otherwise in the course plan. If you miss multiple classes, the Director of Academic Support and the Director of Student Affairs will be notified. Absences will jeopardize your grade and your standing at DIS.  Allowances will be made in cases of illness, but in the case of multiple absences, you will need to provide a doctor’s note.


Field Studies May Include

  • Board game playing
  • Visit to the AI and robotics facilities at the Technical University of Denmark (DTU)
  • Visit to CIBS – Center for Information and Bubble Studies, University of Copenhagen (KU)
  • Visit to IBM including exercises on IBM chatbot technology
  • Visit to LEO Innovation Lab developing AI-based health apps

Academic Regulations  

Please make sure to read the Academic Regulations on the DIS website. There you will find regulations on:

Course Summary:

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