Learning outcomes for the Master’s in Mathematical Data Science (120 ECTS)

Scientific qualification

Learning Outcome	Implementation	Achievement
Graduates are trained in analytical thinking, possess a highly developed capacity for abstraction, universally applicable problem-solving skills, and the ability to structure complex relationships.	Lectures with tutorials, seminars, study groups, dissertation	Tutorial assignments, written examinations, individual oral examinations, presentations, dissertation
Graduates are able to familiarise themselves independently, with the aid of specialist literature, with current areas of research in mathematics, in particular data science and artificial intelligence.	Seminars, study groups, thesis	Presentations, thesis
Graduates are able to present their knowledge, ideas and solutions to complex problems in a comprehensible manner to a specialist audience.	Seminars, study groups, exercises	Presentation of exercise tasks, lectures
Graduates possess the specialist knowledge, ways of thinking and working, and methodological skills required for independent academic work, particularly for doctoral studies in the field of applied mathematics, data science or artificial intelligence.	Seminars, study groups, lectures, exercises, thesis	Exercises, written examinations, individual oral examinations, presentations, thesis
Graduates are familiar with the rules of good academic practice and are able to apply them in extensive academic work.	Thesis	Thesis
Graduates possess in-depth knowledge of current areas of applied mathematics and data science and are able to apply advanced methods in these fields with confidence.	Seminars, study groups, lectures, tutorials, thesis	Tutorial exercises, written examinations, individual oral examinations, presentations, thesis
Graduates possess in-depth knowledge and an overview of current research in at least one subfield of mathematics.	Study groups and seminars, thesis	Presentations, thesis
Graduates are familiar with current fields and modern methods in applied data science and artificial intelligence.	Lectures, tutorials, study groups, seminars, practicals	Exams, practical report, project work, presentations, assignments, oral examinations

Ability to take up employment

Learning Outcome	Implementation	Achievement
Graduates are trained in analytical thinking, possess a strong capacity for abstraction, universally applicable problem-solving skills, and the ability to structure complex relationships.	Lectures with exercises, seminars, study groups, thesis	Exercises, written examinations, individual oral examinations, presentations, thesis
Graduates are able to formulate and present their knowledge, ideas and problem-solving approaches in a clear and accessible manner tailored to specific audiences.	Seminars, exercises	Presentation of exercise tasks, presentations
Graduates are able to identify, structure and model complex data science problems, develop solutions using mathematical methods of data science, and interpret and evaluate these results.	Seminars, study groups, lectures and exercises in the fields of applied mathematics, computer science and data science, placements, thesis.	Exercises, written examinations, individual oral examinations, presentations, placement report, thesis
Graduates demonstrate strong perseverance in solving complex problems.	Exercises, thesis	Exercise tasks, thesis
Graduates are able to work constructively and goal-orientedly in teams, whilst taking on responsibility.	Seminars, study groups, internships	Presentations, internship report
Graduates are able to independently, efficiently and systematically explore new fields of knowledge and current developments in the field of data science and artificial intelligence.	Seminars, study groups, thesis	Presentations, thesis
Graduates can implement the data science methods they have learnt and are confident in using mathematical software and machine learning software packages.	Exercises, Internships, Seminars, Study Groups, Thesis	Programming tasks, Project work, Lectures, Internship report, Thesis
Graduates possess the ability to take responsibility for shaping projects within interdisciplinary teams in the fields of mathematics, computer science and empirical sciences.	Internships, study groups	Lectures, internship report
Graduates are familiar with the theoretical and practical advantages and disadvantages of advanced algorithms in artificial intelligence and machine learning and can apply these precisely to practical problems.	Lectures, tutorials, seminars, practicals, study groups	Tutorial exercises, programming tasks, project work, presentations, practical report

Personality development

Learning Outcome	Implementation	Achievement
Graduates are trained in analytical thinking, possess a highly developed capacity for abstraction, universally applicable problem-solving skills, and the ability to structure complex relationships.	Lectures with tutorials, seminars, study groups, thesis	Tutorial assignments, written examinations, individual oral examinations, presentations, thesis
Graduates are able to critically reflect upon and evaluate social and economic developments in the field of data science and artificial intelligence.	Lectures, practicals, seminars, study groups, thesis	Presentations, practical report, thesis
Graduates are able to play a proactive role in participatory processes.	Involvement in the student council and other student organisations, participation in committees and bodies	Committee work and meetings
Graduates demonstrate strong perseverance in solving complex problems.	Exercises, thesis	Exercise tasks, thesis
Graduates are able to formulate complex ideas and proposed solutions in a way that is generally understandable and present them professionally.	Seminars, study groups, exercises, work placements	Lectures, presentation of solutions to exercise tasks, work placement report