Studying artificial intelligence

Young African American female engineer operating a robotic welding arm machine in the warehouse factory.
© Getty Images/klingsup

Systems based on artificial intelligence have long played an important role all across society: apps are used to check your pulse or create playlists, robots assist during surgeries, shopping platform providers use AI to predict the preferences of their customers. The text processing tool ChatGPT has lately drawn great attention to language-based AI in particular: everybody can now see for themselves, whether it really is a better option for writing essays, blog posts or songs.

The field of artificial intelligence (AI) is dedicated to automating intelligent behaviour, and is among the key future technologies. AI applications can analyse and combine vast amounts of data in a very short time. Intelligent systems apply human abilities such as perception, thinking, planning, learning, speaking or action to machines, robots or software systems, thus enabling them to independently process and solve problems – in smart homes, as well as in networked production facilities, agriculture and transport.

AI is an interdisciplinary technology

AI-based applications are fuelling digital transformation. AI experts are sought-after around the world, even now, and demand is expected to increase further over the next few years. Many universities and universities of applied sciences (HAW) in Germany are already offering related study programmes. As a branch of computer science, artificial intelligence is frequently integrated in disciplines such as robotics, computational linguistics and data science, while dedicated study programmes are still rare. AI is an interdisciplinary technology, which is why studies in this field tend to follow a multidisciplinary approach with a wide range of focus areas such as mechatronics, medicine or cognitive sciences.

Karlsruhe University of Applied Sciences (HKA) is launching its new bachelor´s degree course for the 2023/24 winter semester. Instead of considering AI merely with regard to data processing, this programme focusses on practical application. The course includes elements from the fields of electrical engineering, information technology and mechanical engineering, as well as covering ethical and societal aspects. An increasing use of intelligent systems certainly gives rise to questions concerning safety and responsible use of the technology.

Data science is a relatively young discipline that links the core disciplines computer science, mathematics and statistics and uses AI-based methods to facilitate decision-making processes. Data scientists analyse comprehensive data sets in order to generate information and derive recommendations for action. These include business decisions, product recommendations or indications regarding the success of medical treatments. There are over 300 study programmes in this field in Germany, for example at the and . Graduates are needed across all areas, from business through to research.

AI research: close links to industry

ChatGPT is currently a very prominent example of a language processing model from the area of computational linguistics. The study discipline that is also known as Natural Language Processing (NLP) examines and analyses language aiming to “teach” computers this gained understanding of language. The Center for Information and Language Processing at the Ludwig Maximilian University of Munich offers a bachelor´s degree course in computational linguistics with computer science, philosophy, ‘language, literature and culture’ or German as a foreign language as available minor subjects. The English-language branch offers courses on subjects including parsing*, text technology and grammar formalism in which the humanities and natural sciences are closely linked.

There is a wide range of study programmes that deal with the diverse areas of application of AI already, and it keeps growing. Across Germany, top-class AI experts from around the world are conducting research dedicated to innovative developments in the key technologies of AI and machine learning (ML). German universities are cooperating through inter-institutional networks, for example, by pooling their strengths at the . The three graduate schools ELIZA, relAI and SECAI maintain close contact with the business sphere and non-university research facilities. Companies are involved in training right from the start, making it easier for talents in the area of AI to transfer from academic research to the business world.

*The term parsing describes the decomposition of an object into its individual parts.

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