AI for Managers (WiSe, Master, 6 ECTS)

AI for Managers


Content
The course aims to give an introduction to AI algorithms and coding exercises. Students learn to plan, implement and evaluate AI in applied settings in order to generate value from data forsociety, corporations and individuals. This serves the pressing need of firms to improve their efficiency – such as customersatisfaction, competitive advantage – by leveraging the growing amounts of structured and unstructured data. Please note that sufficient programming skills are required (e.g. R, Python).

Students
MMT
MBR

Format
Onsite and online course (either or, tbd)

Literature
  • James, Witten, Hastie & Tibshirani (2013): An Introduction to Statistical Learning: With Applications in R. Springer
  • Sharda, Delen & Turban (2014): Business Intelligence: A Managerial Perspective on Analytics. Pearson
Enrolment
Moodle self enrolment, enrolment key via LSF

Advanced AI in Businesses and Organizations (WiSe, Master, 6 ECTS)

Advanced AI in Businesses and Organizations


Content

In this online course, students will implement an advanced machine learning project. The machine learning project should be of value to the decision-making in businesses, organizations, and society. This is an advanced course for specialization.

Students
  • MMT
  • MBR
  • M.Sc.
Format

Online course

Seminar Paper

Deliverables will be a paper that involves actual machine learning results (with codes in the appendix) and a video presentation. Students will need to advance their knowledge on their own with the provided materials.

Literature
    Enrolment

    Moodle self enrolment, enrolment key via LSF

    Digital Technologies, Business Analytics and Management (WiSe, Master, Fachspezifische Grundlagen, 9 ECTS)

    Digital Technologies, Business Analytics and Management


    Content

    Overall, the course provides students with a comprehensive overview of how digital technologies are used in modern business settings. It equips them with the skills they need to take advantage of these technologies and become more successful managers.

    Students
    • M.Sc. Betriebswirtschaftslehre
    Requirements

    No specific requirements

    Literature
    • James, Witten, Hastie & Ribshirani. 2013. An Introduction to Statistical Learning: With Applications in R. Springer.
    • Sharda, Delen & Turban. 2014. Business Intelligence: A Managerial Perspective on Analytics. Pearson.
        Enrolment

        Self-enrolment in Moodle, enrolment key via LSF

        Introduction to AI (WiSe, Bachelor, 6 ECTS)

        Introduction to AI


        Content
        The course aims to give an introduction to AI algorithms and coding exercises. Students learn to plan, implement and evaluate AI in applied settings in order to generate value from data forsociety, corporations and individuals. This serves the pressing need of firms to improve their efficiency – such as customersatisfaction, competitive advantage – by leveraging the growing amounts of structured and unstructured data. Please note that sufficient programming skills are required (e.g. R, Python).

        Students
        B.Sc.

        Format
        Onsite and online course (either or, tbd)

        Literature
        • James, Witten, Hastie & Tibshirani (2013): An Introduction to Statistical Learning: With Applications in R. Springer
        • Sharda, Delen & Turban (2014): Business Intelligence: A Managerial Perspective on Analytics. Pearson
        Enrolment
        Moodle self enrolment, enrolment key via LSF

        AI Tools for Management and Social Science (WiSe, Bachelor, Hauptseminar, 6 ECTS)

        AI Tools for Management and Social Science


        Content

        In this seminar, students will familiarize with a specific AI tool relevant for management and social science research. They will review a specific topic, write a report and give a presentation on their findings.

        Please note: The successfull completion of this course is a prerquisite to write your bachelor thesis at the Institute of AI in Management.

        Students
        • B.Sc. Betriebswirtschaftslehre
        Seminar Paper

        Deliverables will be a seminar paper (22,200 characters, including spaces) and a video-presentation (15 minutes).
            Requirements

            Sufficient programming skills required (e.g. R, Python), such as taught in one of our previous courses (e.g. "Introduction to AI").

            Enrolment
            1. Please register via Hauptseminaranmeldung
            2. Accepted students are asked to self enroll via Moodle, enrolment key in LSF

            Business Analytics in Practice (SoSe, Master, Projektkurs, 12 ECTS)

            Business Analytics in Practice


            Content

            The project course offers students the opportunity to work on a real business problem during the semester. Students are assigned to teams (3-5 per team) , collaborating closely with a company, working on a problem statement of practical relevance, and collecting all their findings in a presentation and a report.

            Students should expect that they have to schedule regular meetings with the partner company. The format will be determined by the company but expected to be most likely in person and at the company.

            Students
            • M.Sc. Betriebswirtschaftslehre

            Report and Presentation

            • Report (44,400 – 66,600 characters, including spaces)
            • Presentation (30-50 minutes)


                Enrolment
                1. Please register via Projektkursanmeldung
                2. Accepted students will be enrolled to the Moodle course by us

                Requirements
                • Previous participation in one of our courses such as Digital Technologies, Business Analytics and Management (FSG).
                • Sufficient programming skills required (e.g. R, Python), such as taught in one of our previous courses (e.g. "Introduction to AI").

                AI for Good (SoSe, Master, 6 ECTS)

                AI for Good


                Content

                In this seminar students will apply AI methods on real world data to solve societal problems, by analyzing data and applying different AI methods to visualize and gain insights. Topics are selected with a focus on having a positive impact on society. Students are encouraged to work in teams of four.


                Students
                • MMT
                • Master programs at the faculty of mathematics, informatics and statistics

                Seminar Paper

                Deliverables will be a seminar paper (22,200 characters per Person, including spaces) and a video-presentation (15 minutes per Person).


                    Enrolment

                    Moodle self enrolment, enrolment key via LSF


                    Requirements

                    Sufficient programming skills required (e.g. R, Python), such as taught in one of our previous courses ("AI for Managers", "Introduction to AI", etc.).


                    Managerial AI (SoSe, Master, 6 ECTS)

                    Managerial AI


                    Content

                    In this seminar, students will apply AI methods on real world data to solve managerial problems (e.g. prediction of financial outcomes, internet search trends, etc.). Participants will analyze data and apply different AI methods to visualize and gain insights on their data. Students are encouraged to work in teams of two.


                    Students
                    • M.Sc. Betriebswirtschaftslehre

                    Seminar Paper

                    Deliverables will be a seminar paper (22,200 characters per Person, including spaces) and a video-presentation (15 minutes per Person).


                        Enrolment

                        Moodle self enrolment, enrolment key via LSF


                        Requirements

                        Sufficient programming skills required (e.g. R, Python), such as taught in one of our previous courses ("AI for Managers", "Introduction to AI", etc.).


                        Methods for AI (SoSe, Master, 6 ECTS)

                        Methods for AI


                        Content

                        In this seminar, students will discuss a specific AI method and its application in practice. Participants will study the theoretical foundations of the method, and discuss how to apply it to data.


                        Students
                        • M.Sc. Betriebswirtschaftslehre
                        • MMT

                        Seminar Paper

                        Deliverables will be a seminar paper (22,200 characters, including spaces) and a video-presentation (15 minutes).


                            Enrolment

                            Moodle self enrolment, enrolment key via LSF


                            Requirements

                            Sufficient programming skills required (e.g. R, Python), such as taught in one of our previous courses ("AI for Managers", "Introduction to AI", etc.).


                            AI Tools for Management and Social Science (SoSe, Bachelor, Hauptseminar, 6 ECTS)

                            AI Tools for Management and Social Science


                            Content

                            In this seminar, students will familiarize with a specific AI tool relevant for management and social science research. They will review a specific topic, write a report and give a presentation on their findings.

                            Please note: The successfull completion of this course is a prerquisite to write your bachelor thesis at the Institute of AI in Management.


                            Students
                            • B.Sc. Betriebswirtschaftslehre

                            Seminar Paper

                            Deliverables will be a seminar paper (22,200 characters, including spaces) and a video-presentation (15 minutes).


                                Enrolment
                                1. Please register via Hauptseminaranmeldung
                                2. Accepted students are asked to self enroll via Moodle, enrolment key in LSF

                                Requirements

                                Sufficient programming skills required (e.g. R, Python), such as taught in one of our previous courses (e.g. "Introduction to AI").