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2018/2019  KAN-CINTO1820U  Artificial Intelligence and Robotics

English Title
Artificial Intelligence and Robotics

Course information
Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Full Degree Master
Duration One Semester
Start time of the course Spring
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc/MSc in Business Administration and Information Systems, MSc
Course coordinator
  • Daniel Hardt - Department of Management, Society and Communication (MSC)
Main academic disciplines
  • Information technology
  • Innovation
Teaching methods
  • Blended learning
Last updated on 01-10-2018

Relevant links
Learning objectives
  • Explain and analyze the key ideas and techniques underlying Artificial Intelligence technologies
  • Explain and analyze the key ideas and techniques underlying Robotics technologies
  • Demonstrate the ability to implement AI and Robotics technologies using basic programming and machine learning
  • Reflect on the societal and business impact of AI and Robotics technologies
Course prerequisites
Basic programming skills and knowledge of machine learning
Examination
Artificial Intelligence and Robotics:
Exam ECTS 7,5
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance.
Individual or group exam Individual oral exam based on written group product
Number of people in the group 2-5
Size of written product Max. 15 pages
Assignment type Project
Duration
Written product to be submitted on specified date and time.
20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-step scale
Examiner(s) Internal examiner and second internal examiner
Exam period Summer
Make-up exam/re-exam
Same examination form as the ordinary exam
Students can submit the same project or they can choose to submit a revised project.
Course content and structure

AI and Robotics are poised to transform the business and technology landscape, and it has become essential for business leaders to understand the key technologies and concepts involved. This course covers several of the main AI and robotic technologies, including natural language processing, image recognition, and autonomous vehicles.  The primary focus is technical, and students are expected to be able to program in Python or a similar language, and to understand and be able to implement machine learning techniques such as classification and regression. The business impact, as well as societal and ethical topics, will also be considered.
Description of the teaching methods
AI and Robotics are poised to transform the business and technology landscape, and it has become essential for business leaders to understand the key technologies and concepts involved. This course covers several of the main AI and robotic technologies, including natural language processing, image recognition, and autonomous vehicles. The primary focus is technical, and students are expected to be able to program in Python or a similar language, and to understand and be able to implement machine learning systems such as classification and regression. The business impact, as well as societal and ethical topics, will also be considered.
Feedback during the teaching period
Weekly feedback on hands-on exercises. Feedback on plans for final project. Weekly office hours.
Student workload
Lectures 20 hours
Exercises 10 hours
Class Preparation 116 hours
Exam and Preparation for Exam 60 hours
Total 206 hours
Expected literature

The literature can be changed before the semester starts. Students are advised to find the literature on LEARN before they buy the books.

 

Alan Turing (1950) Computing Machinery and Intelligence

 

Ferruci et al (2010) Building Watson: An Overview of the Deep QA Project

 

Halavy et al. (2009) The Unreasonable Effectiveness of Data. Intelligent Systems, 24(2)
 
Last updated on 01-10-2018