Artificial Intelligence and Robotics

STR459 Artificial Intelligence and Robotics

Spring 2024

  • Topics

    Artificial intelligence (AI) creates new opportunities for current and future of the societies and businesses. Such opportunities can be observed in a variety of applications ranging from early development of mobile phones with noise cancelation to modern applications such as automated robotic surgery. Youtube, as an example of an online business, heavily rely on AI techniques to process a massive amount of data produced by users in their everyday interactions with this platform when consuming video content. Adopting AI techniques enables this platform to obtain a deep understanding of the personal needs and preferences of the users and exploit them to generate video recommendations for users. In Amazon 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, Amazon generates personal promotions for users and offers them to enhance its sales. Other examples include AI algorithms integrated into modern cameras to recognize the faces and objects within photos, or AI machines playing chess against world champions at a level that is beyond their capabilities. Finally, the automated tools empowered by advanced AI to trade on the stock market can be another relevant example of AI, automating a task with no need for human involvement.

    This course is designed to provide the students with an overall view of the advancement in AI techniques while enabling the students to practice the development of these techniques. Such techniques will be capable of performing complex tasks, such as predicting human behaviors or clustering objects based on their attributes. The course will primarily focus on Python programming as the most popular language 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 language, and can effectively use them with the goal to gain 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, & business
    • A quick review of Python programming
    • Exploratory data analysis using Python language
    • Building and evaluating predictive models with Python (regression, 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:


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


    • 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, guest lectures, group seminars, and a project assignment (semester assignment).

  • Restricted access


  • Recommended prerequisites

    A programming knowledge on Python is strongly recommended (equivalent to what is taught in  BAN401 Applied Programming and Data Analysis for Business). An interest in smart technology and data science 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). An interest in smart technology and data science is an advantage.

  • Compulsory Activity


  • Assessment

    The exam comprises a project assignment in groups of up to 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


ECTS Credits
Teaching language

Spring. Will be offered spring 2024.

Course responsible

Associate Professor Mehdi Elahi, Departement of Strategy and management