These are the requirements for the Bachelor's Artificial Intelligence and Machine Learning

For the B.Sc. Artificial Intelligence and Machine Learning at Wilhelm Bücher University, there are various ways to access:

Access option No. 1: You have the general university entrance qualification (Abitur), the university of applied sciences entrance qualification, or the subject-specific university entrance qualification.

Access option No. 2: You have a university admission qualification recognized as equivalent by the Hessian Ministry of Culture (e.g. a master's degree or a qualification as a state-certified technician).

Access option No. 3: Auditing as a guest student: You start your guest studies at our university without the mentioned three access routes and after 2 semesters of achievement, you take the university entrance exam (HZP). For this, you must meet all the following requirements:

1. You have completed a training of at least two years in a field related to the desired course of study as regulated by the Vocational Training Act, Craft Code, or federal or state law.
2. You have subsequently worked for at least two years full-time in a field related to the desired course of study.

If you are aiming for a course of study that is not related to the training or professional activity you have completed, then the knowledge acquired through training and professional activity must be expanded or deepened through qualified further education with a workload of at least 400 hours in a field related to the desired course of study.

After successfully passing the university entrance exam (HZP), we will change your status from guest student to regular student.

These are the study contents and the course of study

Your Bachelor's degree programme in Artificial Intelligence and Machine Learning at the Wilhelm Büchner University is structured in a modular way. You will study thematically closed subject areas (modules) to which credit points are assigned according to the European Credit Transfer System (ECTS). The number of credit points assigned to each module depends on the scope of a module and the associated workload. All the credit points you earn will be credited to you and you will receive a certificate. Your achievements are thus comparable and recognized - also internationally.

The course of study is structured as follows:

• 1st semester: Fundamentals of Computer Science, Fundamentals of Object-Oriented Programming, Mathematical Foundations for Computer Scientists, Fundamentals of Business Administration and Legal Foundations, Introduction Project
• 2nd semester: Fundamentals of Software Engineering, Advanced Mathematics, Introduction and Applications of Artificial Intelligence, Description Logic
• 3rd semester: Methods of Machine Learning, AI Programming, Computer Vision with Deep Learning, Project Management and Scientific Work
• 4th semester: Database Systems, Information Systems and Business Intelligence, Digital and Microcomputer Technology, Elective subject I: Cross-Subject Competencies
• 5th semester: Data Visualization and Tools, Big Data and Data Science: Methods and Technologies, Smart Factory, Communication and Leadership, Project Work
• 6th semester: Elective Area II: Module 1, Elective Area II: Module 2, AI Applications and Ethics, Bachelor Thesis including Colloquium

You can choose the Elective Module I from these topics: Intercultural Communication, Social Media, IT Management and Law, Fundamentals of Innovation and Technology Management, Controlling and Quality Management.

You can choose the Elective Module II from these topics: Applications in Information Management, Introduction to App Development, Introduction to IT Security, Design of Interactive Systems, Information Broking and Research, Methods and Techniques of Knowledge Management, Multimedia Applications, Software Architecture, Advanced Programming, Knowledge Organization and Information Retrieval, Operating Systems, Information Technology, Distributed Systems, Design of Digital Transformation, DevOps for AI.

This is how long the Bachelor's programme at Wilhelm Büchner University lasts

The distance learning programme in Artificial Intelligence and Machine Learning lasts a total of 6 academic semesters, which corresponds to a standard period of study of 3 years or 36 months. You can extend the supervision period by 18 months free of charge.

These services of the Wilhelm Büchner University contribute to your graduation within the standard period of study:

• Start of studies at any time
• Individual learning pace
• No forced breaks due to semester breaks
• Study plan and content tailored to distance learning
• Motivated and highly qualified lecturers
• Comprehensive, personal support and service concept

These personal factors also have a positive influence on the duration of studies:

• School and academic background
• Your willingness and ability to learn
• The proximity of your professional education or activity to the content of the study
• Professional and personal framework conditions