Teaching the next generation of AI experts

The chair of AI in Management is engaged in developing, implementing and evaluating AI to improve management. This is also what we try to deliver to students through our teaching. Our focus is on AI algorithms and coding.

Courses

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Courses in Summer Semester

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All courses and assessments are in English!

Master

Bachelor

Course Design

In line with our digital focus, we apply a digital and innovative teaching approach and course design. All materials and interactions are coordinated via Moodle. Courses and assessments are in English. We practice an annual rotation of courses, with the exception of the Hauptseminar, which takes place every semester.

Course Sequence

For our Master's courses, we recommend the following sequence (1) AI for Managers [MMT & MBR] or Digital Technologies, Business Analytics and Management [M.Sc. BWL] => (2) Advanced AI in Businesses and Organizations => (3) Research in AI and Management.

Courses in Winter Semester

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All courses and assessments are in English!

Master

Bachelor

Course Design

In line with our digital focus, we apply a digital and innovative teaching approach and course design. All materials and interactions are coordinated via Moodle. Courses and assessments are in English. We practice an annual rotation of courses, with the exception of the Hauptseminar, which takes place every semester.

Course Sequence

For our Master's courses, we recommend the following sequence (1) AI for Managers [MMT & MBR] or Digital Technologies, Business Analytics and Management [M.Sc. BWL] => (2) Advanced AI in Businesses and Organizations => (3) Research in AI and Management.

Theses

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M.Sc. Thesis

We offer inovative and impactful topics (e.g. AI for Good, AI for Medicine, Causal Machine Learning, etc.) that we jointly select to fit the interests and study focus of students. Due to the double-affiliation to the department of Mathematics, Informatics and Statistics, we also welcome students from there to apply for a Master thesis at our chair.

Requirements

  • For business students:
    • Substantial programming skills
    • Prior participation in our courses: (1) AI for Managers [MMT] or Digital Technologies, Business Analytics and Management (FSG) [M.Sc. BWL]; and (2) Advanced AI in Businesses and Organizations (Highly recommended)
  • For students in mathematics, informatics and statistics: No requirements

Specifications

  • English language
  • LaTeX format
  • Topics are provided by the chair
  • Industry-based theses are possible, but must be organized by students themselves (please follow the same application procedure as for regular theses below)

Application

  • Application via email ai@som.lmu.de
  • Provide the following documents and information: (1) Curriculum Vitae, (2) transcripts (Master & Bachelor), and (3) preferred start date
  • You can also state our interestes / preference of thesis topics => Please check the tab "Topics"

Colloquium

  • To support research-oriented focus of the theses, we regularly hold a keynote series around "AI in management". Thesis students are expected to participate.

Tutorial

Download our thesis tutorial (PDF, 179 KB)

B.Sc. Thesis

We offer inovative and impactful topics (e.g. AI for Good, AI for Medicine, Causal Machine Learning, etc.) that we jointly select to fit the interests and study focus of students. Due to the double-affiliation to the department of Mathematics, Informatics and Statistics, we also welcome students from there to apply for a Bachelor thesis at our chair.

Requirements

  • For business students:
    • Basic programming skills
    • Prior participation in our course Introduction to AI (Highly recommended)
  • For students in mathematics, informatics and statistics: No requirements

Specifications

  • English language
  • LaTeX format
  • Topics are provided by the chair
  • Industry based theses possible, but must be organized by students themselves

Application

  • Application via email ai@som.lmu.de
  • Provide the following documents and information (1) Curriculum Vitae, (2) transcript, (3) preferred start date

Colloquium

  • To support research-oriented focus of the theses, we regularly hold a keynote series around "AI in management". Thesis students are expected to participate.

Tutorial

Download our thesis tutorial (PDF, 179 KB)

Thesis Topics and Examples

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This is a list of current topics and broader research areas we are interested in. They apply to both Bachelor and Master theses.

Social Media Analytics

  • Monitoring political ads on social media (data preparation)
  • Understanding the role of social media ads in election outcomes (regression analysis)
  • Identifying and mitigating toxic content (e.g., fake news, hate, speech, propaganda) on social media with machine learning (regression analysis / machine learning)

Human-AI Collaboration

  • Understanding the perception of users towards generative AI (survey/field experiment)

Business Analytics

  • Understanding the innovation potential of generative AI (survey/field experiment)
  • Optimal budgeting for marketing campaigns (advanced machine learning)

AI for Good

  • Understanding the success of power plants in Africa (regression analysis)
  • Monitoring aid development for healthcare (statistical analysis)
  • Applied causal machine learning for treatment effect estimation in intensive care units

Causal Machine Learning

[Faculty of Mathematics, Informatics and Statistics only]

  • Causal representation learning for treatment effects in medicine
  • Causal sensitivity analysis
  • Reliable off-policy learning for treatment decision-making

Examples of successful, previous theses at our Institute

References

We are happy to provide students of our chair with a reference letter, if they fulfill the following requirements: (1) Prior participation in our courses, (2) Successful completion of the exams. Please contact ai@som.lmu.de with your request.

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