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Information Systems and Applied Computer Sciences

B. Sc. Artificial Intelligence and Data Science

  1.  University of bamberg
  2. Faculties
  3. Information Systems and Applied Computer Sciences
  4. Studies
  5. Degree programmes offered
  6. B. Sc. Artificial Intelligence and Data Science
  7. Qualification Goals

Qualification Goals of the B.Sc. in Artificial Intelligence & Data Science

Upon completion of their studies, students have achieved the following qualification goals.

Scientific qualification:

Graduates

  • are able to abstract to a high degree, think critically and solve problems analytically and structurally in a pronounced form.
  • have familiarised themselves with relevant techniques and methods from mathematics, statistics, logic, computer science and programming and can apply these fundamentally in the field of Artificial Intelligence (AI) and Data Science (DS).
  • are familiar with the fundamentals, techniques and applications of AI and DS as a result of attending the basic scientific modules and can rely on a profound methodological understanding.
  • have developed a profile-specific core competence in one (or up to three, depending on the profile chosen) of the AI or DS research areas represented in Bamberg, building on a broad basic competence in AI and DS, and can apply profile-specific methods of the theoretical foundations of computer science, AI, as well as theories and methods of programming intelligent agents and the mathematics of data science in a context-related manner.
  • are able to apply the specialist knowledge they have acquired as well as the interdisciplinary knowledge, e.g. the competences relating to the ethical context of a digital society, in a reflected manner and on the basis of a needs analysis, as well as to further develop these specialist competences.
  • are able to effectively apply basic programming and modelling techniques in development projects based on the skills they have acquired in exercises in specified specialist modules.
  • are able to analyse, design, implement and validate complex, intelligent agents and methods of data analysis as well as create and present technical documentation based on their comprehensive technical understanding.
  • know the generally recognised principles of scientific work and are able to understand and present scientific issues in AI and DS under guidance, as they have demonstrated in their project work and Bachelor's thesis.
  • have shown in their Bachelor's thesis that they can independently design a scientifically orientated thesis in the field of AI and DS by applying the specialist knowledge they have acquired to a derived research question using scientific methods and observing the principles of good scientific practice.

Qualification for employment:

Graduates

  • have demonstrated in practical exercises and projects that they have mastered the techniques of programming and modelling AI and DS applications and can use them appropriately in a given application context.
  • can work well together in teams and communicate complex contexts and problem solutions in a subject-specific and interdisciplinary manner, as they have demonstrated in group work and presentations.
  • can take on project-orientated management tasks and integrate those involved, taking into account the respective group situation.  
  • are able to fulfil the requirements placed on the intra- and inter-company integration of intelligent processes and evaluate their ethical and social implications on the basis of their successful participation in corresponding specialist modules.
  • are fundamentally able to use scientific methods to tackle industry-specific challenges and develop innovative solutions in the context of AI and DS.

Personal development:

Graduates

  • are able to analyse AI and DS problems on their own and in a team, develop and refine suitable solutions and communicate them professionally, as they have learned to do in exercises, seminars and project work.
  • can acquire extensive specialised knowledge both under supervision and independently and apply it in practical projects.
  • are able to assess their own professional skills as well as their personal and social competences and already have ideas about their further development as part of a lifelong learning process.
  • are familiar with English-language specialist terminology as a result of studying specialist literature and participating in language-based modules and can communicate using this specialist terminology in a logically consistent manner.
  • are familiar with the basic principles of scientific ethics and data protection and can play a decisive role in shaping social processes with a sense of responsibility and a democratic sense of community.
  • are aware of their responsibility with regard to the social impact of modern information technologies and can appropriately reflect on the ethical and legal aspects of AI and DS.
  • have developed a clearly structured professional self-image.