School of Advanced Professional Studies

The School of Advanced Professional Studies (SAPS) offers a range of programs and courses for professional development and continuing education.

Programs

• Actuarial Science: A program focused on the study of actuarial science and its applications.
• Artificial Intelligence for Connected Industries: A program exploring the use of artificial intelligence in various industries.
• Biopharmaceutical and Medical Technology Sciences: A program combining biopharmaceutical and medical technology sciences.
• Business Analytics: A program focused on business analytics and data-driven decision making.
• Instructional Design: A program on designing effective instructional materials and experiences.
• Sensor System Technology: A program focused on the development and application of sensor systems.
• Advanced Oncology: A program focused on advanced topics in oncology.

Continuing Education Formats

• Microcredentials: Short, focused courses on specific topics, including:
  • Microcredential series on teaching
  • Microcredential series on learning
  • Microcredential series on digital topics
  • Microcredential series on life insurance
• Certificate Courses: In-depth courses leading to a certificate, including:
  • Certificate of Advanced Studies (CAS) in various fields such as actuarial science, biopharmaceutical and medical technology sciences, and business analytics.
  • Diploma of Advanced Studies (DAS) in fields like actuarial science, business analytics, instructional design, sensor system technology, and drug research and biomedicine.

Projects

• EduNEXUS BW: A project focused on education and networking.
• Artificial Intelligence for Connected Industries: A project exploring AI applications in industries.
• 2LIKE: A project including workshops on adaptive learning in higher education.
• Hochschulweiterbildung@BW: A project on continuing education at universities in Baden-W僡ttemberg.
• Weiterbildungsberatung: Counseling services for continuing education.
• Archiv der abgeschlossenen Projekte: An archive of completed projects.

About Us

• Our Team and Contact: Information about the team and how to contact them.
• Structure and Governance: Details about the organizational structure and governance of SAPS.
• Cooperations and Memberships: Information on partnerships and memberships.
• Job Offers: Listings of available positions.
• Information Materials: Access to brochures, maps, statutes, and FAQs.
• Public Relations and Press: Newsletters, annual reports, press articles, and press releases.
• Publications: Articles in professional journals, book contributions, monographs, concepts, and guidelines.

Module Handbook

The module handbook provides detailed information on the courses offered by SAPS.

Module Contents

• Foundations of Machine Learning with Python: A module teaching fundamental methods of machine learning and their application in Python.
  • Module Group: Informatik
  • Description: This module covers basic concepts of machine learning, including supervised and unsupervised learning algorithms, and their implementation in Python.
  • Online Sessions: Weekly online sessions on Tuesday evenings.
  • Dates: Specific dates for the online sessions are provided.
• Learning Objectives:
  • Subject Competence: Understand basic concepts of machine learning, evaluate model quality, apply Python libraries for machine learning, choose appropriate ML methods for given problems, and prepare data for ML procedures.
  • Method Competence: Apply the CRISP-DM process to analytical problem-solving, design, implement, and test solution approaches, and solve application problems using suitable machine learning methods.
  • Social and Self-Competence: Develop and discuss solutions for machine learning tasks, work in small groups, assess own analytical and conceptual skills, and reflect on strengths and weaknesses.

Learning Setting

• Flipped Classroom: The online study takes place in self-study, with video lectures, documented code examples, and practical exercises available.
• Weekly Online Sessions: Additional support is provided during weekly online office hours.

Prerequisites

• First University Degree: A prerequisite for the module.
• Content: Basic knowledge of Python for data science is desirable, with a crash course available in the first learning unit.

Technical Requirements

• Recommended Hardware and Software: Specifications for desktop computers, notebooks, headsets, internet browsers, and internet access are provided.
• Contact: For questions about technical requirements, contact information is available.

Certification

• Certificate: Upon successful completion of the module, a certificate and a supplement detailing the module's content are awarded.
• ECTS Points: Equivalent to 3 ECTS points.

Fees

• Study Fees: Information on study fees for enrolled students and for attending individual modules in continuing education programs.

Instructor

• Prof. Dr. Reinhold von Schwerin: Instructor for the module, affiliated with the Technical University of Ulm.

Funding

• Ministry for Social Affairs and Integration Baden-W僡ttemberg: Funding from the European Social Fund and the Ministry for Science, Research, and Arts Baden-W僡ttemberg.
• Project "Data Literacy and Data Science for the Mittelstand": The certificate course was developed within this project framework.

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Overview:

University of Ulm is a public research university located in Ulm, Germany. It is known for its strong focus on research, study, and knowledge transfer. The university boasts a diverse range of academic programs and a commitment to international collaboration.

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Services Offered:

The university offers a comprehensive range of services to support students, including:

Student advisory services:

Providing guidance on academic matters, career planning, and personal development.

Psychosocial Counselling:

Offering support for students facing mental health challenges.

Events for prospective and current students:

Organizing events to inform and engage students.

Application and enrolment services:

Assisting students with the application and enrollment process.

Exam administration:

Managing exam procedures and recognition of achievements.

Continuing education programs:

Providing opportunities for professional development.

International Office:

Supporting international students and fostering global partnerships.

Centre for Educational Development:

Promoting excellence in teaching and learning.

School of humanities:

Offering programs in the humanities and social sciences.

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Student Life and Campus Experience:

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Key Reasons to Study There:

Strong research focus:

The university is renowned for its research excellence, particularly in areas like medicine, engineering, and natural sciences.

International environment:

Ulm University actively promotes international collaboration and welcomes students from around the world.

Modern facilities:

The university provides students with access to state-of-the-art facilities and resources.

Dedicated faculty:

The university boasts a highly qualified and dedicated faculty committed to student success.

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Academic Programs:

University of Ulm offers a wide range of academic programs across various disciplines, including:

Engineering, Computer Science and Psychology:

The faculty offers programs in engineering, computer science, and psychology.

Mathematics and Economics:

The faculty offers programs in mathematics and economics.

Medicine:

The medical faculty offers programs in medicine and related fields.

Natural Sciences:

The faculty of natural sciences offers programs in various scientific disciplines.

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Other:

• The university is recognized for its commitment to family-friendly policies and has received the "audit family-friendly university" certificate.
• Ulm University has been ranked among the top universities in Germany by StudyCheck.
• The university is a member of the "Universities for openness, tolerance and against xenophobia" initiative.