STR459 Artificial Intelligence and Robotics

• Topics

  Artificial Intelligence (AI) creates new opportunities for the current and future of societies and businesses. Such opportunities can be observed in a variety of applications ranging from the early development of mobile phones to modern applications such as automated robotic surgery. Social media platforms, as examples of online businesses, heavily rely on AI techniques to process a massive amount of data produced by users in their everyday interactions with these platforms when reading text and watching videos online. Adopting AI techniques enables these platforms to obtain an understanding of the interests and preferences of the users and incorporate them to generate recommendations for users. In online shops, the data observed from the users purchasing products are analyzed by AI methods to identify a set of potential products that can be purchased by the users in the future. Accordingly, online shops generate promotions for users and offer them the opportunity to enhance sales. Other examples include AI models playing chess against world champions at a level that is beyond any expectation.

  This course is designed to provide the students with an overall view of the advancement in AI techniques while enabling them to practice the development of these techniques. The course will primarily focus on Python programming, which is one of the most popular languages for learning the development of AI. Hence, a background in Python programming will be strongly recommended for the students. More particularly, the course will guide the students to obtain good knowledge on a set of relevant skills, namely, processing data collected in different domains, analyzing the data to understand their characteristics, and building AI models that can predict future data. In addition, the students will get familiar with a set of popular libraries and practical tools developed in Python and can effectively use them with the goal of gaining the above-described knowledge.

  In summary, the course will teach the following topics:

  • A general introduction to AI
  • AI techniques and their potential benefits to individuals, societies, and businesses
  • A quick review of Python programming
  • Exploratory data analysis using Python language
  • Building and evaluating predictive models with Python (e.g., regression, and classification)
  • Building and evaluating recommender systems with Python

  The course will consist of lectures (physical) and group exercises (labs) that focus on practical lessons to develop and use AI techniques. On the basis of the lectures and exercises, the students will work in groups on a project assignment that involves the use of AI and must be submitted as the final exam.

• Learning outcome

  Upon course completion, the student can:

  Knowledge

  • Understand what AI involves.
  • Explain how AI can be used in business development.
  • Discuss recent trends in AI.

  Skills

  • Write a Python program to build AI models
  • Use popular libraries and tools in Python for AI development  

  General competence

  • Understand the organisations of the future and the interaction between humans and technology
  • Disseminate key academic material such as theories, problems and solutions both in writing and verbally

• Teaching

  The course is organised as a combination of frontal lectures (or guest lectures), group seminars, and a project assignment (semester assignment).

• Restricted access

  Due to the technical and practical aspects of this course, there is restricted access at 60 students in this course. All restricted access subjects have an earlier deadline for registration than other ordinary subjects. For more information on access-restricted subjects please see: https://www.nhh.no/for-studenter/adgangsbegrensa-emne/

• Recommended prerequisites

  An interest in smart technology and AI is an advantage.

• Required prerequisites

  Programming knowledge of Python is a requirement (equivalent to what is taught in  BAN401 Applied Programming, and Data Analysis for Business, BAN438 Application Development in Python, and BAN436 Introduction to Python). 

• Compulsory Activity

  None

• Assessment

  The exam comprises a project assignment in groups of 3-5 students together with a written report. The details of the assignment will be handed out during the course and must be submitted by the provided deadline. The groups should be established as soon as the course begins to enable efficient teaching.

• Grading Scale

  Grade scale A-F.

• Computer tools

  Students will need to have access to a computer with an Internet connection. The lectures and group seminars will take place physically. Students will also use a number of (free) tools related to Python. Details of the tools will be provided in the course.

• Literature

  • AI resources available online
  • Research articles on AI
  • Lecture notes