ISM-E1004 - Business Analytics 2, Lecture, 8.1.2024-19.2.2024

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Management Science uses analytical models to help make better business decisions. This course focuses on models for supporting decision making under uncertainty, risk and multiple objectives. After taking the course the student can (i) recognize the types of real-life business problems where the use of models adds value, (ii) interpret results of these models to derive defensible decision recommendations, and (iii) build and solve these models computationally to support business decision making.

Credits: 6

Schedule: 08.01.2024 - 19.02.2024

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Ilkka Leppänen

Contact information for the course (applies in this implementation):

Email: ilkka.j.leppanen@aalto.fi

I am available for consultation meetings outside of lecture hours, room T201 / Teams.

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    Simulation, decision trees, value of information, expected utility theory, risk attitudes, stochastic dominance, risk measures, multi-attribute utility/value theory, modelling uncertainty and multiple objectives in optimization problems.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Coursework and exam

  • applies in this implementation

    There are three individual assignments that together form 50% of the course grade. The exam is 50% of the grade.

Workload

  • valid for whole curriculum period:

    Contact teaching, individual work, exam.

DETAILS

Study Material

  • applies in this implementation

    Course material is delivered via MyCourses and consists mostly of lecture slides.

    The following textbook is recommended as additional reading: Anderson, David R. (David Ray) et al. An Introduction to Management Science ; Quantitative Approaches to Decision Making. 14th ed. Boston, MA, 2016. (Other editions from the same author(s) are also applicable).

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    8 Decent Work and Economic Growth

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Spring III
    2023-2024 Spring III

  • applies in this implementation

    We will use a mix of computational techniques, including spreadsheet modelling and Python/R scripts. Please expect that the assignments require a moderate level of coding to produce programming scripts. The focus is not on programming itself, rather on formulating models for problem solving using modern computational techniques. The teaching sessions will have dedicated time to support students in using these tools.

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof