STR459 Artificial Intelligence and Robotics
Artificial intelligence (AI) creates new opportunities for current and future of the societies and businesses. Such opportunities can be observed in a verity 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 recommendation for users. In Amazon the data observed from the users, purchasing products are analysed by AI methods to identify a set of the potential products that can be purchased by the users in future. Accordingly, Amazon generates personal promotions for users and offers them to enhance its sale. 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 in a level that is beyond their capabilities. Finally, the automated tools empowered by advanced AI to trade on stock market can be another relevant example of AI, automating a task with no need for human involvement.
This course is designed to provide to the students an overall view of the recent advancement in AI techniques, while enabling the student to practice the development of these techniques. Such techniques will be capable of performing complex tasks, such as predicting human behaviours 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 on Python programming will be a requirement for the students. More particularly, the course will guide the students to obtain a good knowledge on a set of relevant skills, namely, processing data collected in different domains, analysing 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.
IIn 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 (digital or 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.
Knowledge - the candidate
- has good knowledge of what AI involves
- has good knowledge of how AI can be used in business development
- is familiar with recent trends in AI
Skills - the candidate
- can write a Python program to build AI models
- can use popular libraries and tools in Python for AI development
General competence - the candidate
- has a good understanding of the organisations of the future and the interaction between humans and technology
- can disseminate key academic material such as theories, problems and solutions both in writing and verbally
The course is organised as a combination of frontal lectures, guest lectures, group seminars, and a project assignment (semester assignment).
A programming knowledge on Python is a requirement (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.
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 provided deadline. The groups should be established as soon as the course begins to enable efficient teaching.
Grade scale A-F.
Students will need to have access to a computer with the Internet connection. The lectures and group seminars can be digital or physical. Hence the students may need access to Zoom app. Students will also use a number of (free) tools related to Python. Details of the tools will be provided in the course.
- AI resources available online
- Research articles on AI
- Lecture notes
- ECTS Credits
- Teaching language
Spring. Available in spring 2022
Associate Professor Mehdi Elahi, Institutt for strategi og ledelse