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

The fundamental aim of Business Analytics is utilizing analytical models to help make better business decisions. This course focuses on optimization models that are commonly used in business applications. After the course the student can (i) recognize the types of real-life business decision problems where use of the models brings added value, (ii) interpret results of these models to derive defensible decision recommendations, and (iii) build and solve these models using relevant software to support business decision making.

Credits: 6

Schedule: 01.11.2021 - 16.12.2021

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Juuso Liesiö

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

Prof. Juuso Liesiö (juuso.liesio(at)aalto.fi)

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:

    Linear programming, network and distribution models, mixed-integer linear programming, non-linear programming.

  • applies in this implementation

    This course focuses on Business Analytics & Management Science methods based on mathematical optimization such as Linear Programming, Mixed-Integer Linear Programming and Non-Linear Programming. These methods are introduced through applications in, for instance, production planning & scheduling, logistics, marketing and finance. The course also introduces approaches for modelling uncertainties and multiple decision objectives in optimization models.


Assessment Methods and Criteria
  • valid for whole curriculum period:

    Assignments 50%, exam 50%.

  • applies in this implementation

    Final points consist of exam points (50%) and assignment points (50%). The final points determine the course grade as follows:  >50p->1, >60p->2, >70p->3, >80p->4, and >90p->5, with the exception that at least half of the exam points are required to pass. These bounds maybe relaxed during final grading.

    There are three assignments with deadlines on roughly the second, fourth and sixth week of the course. Each assignment consists of several problems or cases, which require the use of spreadsheets or other mathematical software to solve. The total points are not equal for all three assignments.



Workload
  • valid for whole curriculum period:

    Contact teaching 36h (no mandatory attendance), individual work 121h, exam 3h. Total 160h (ECTS).

  • applies in this implementation

    Hybrid sessions 36h
    Class preparation 12h
    Assignments 102h
    Preparing for the exam 7h
    Online exam 3h

DETAILS

Study Material
  • valid for whole curriculum period:

    Lecture slides, articles, assignments, computer implementations of mathematical models, and the textbook (An Introduction to Management Science by Anderson et al., 2014, ISBN Code: 978-1-111-82361-0).

  • applies in this implementation

    All material except for the textbook will be available at MyCourses.

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Max. 170 students will be admitted to the course and priority is given to:

    1. BSc students majoring in ISM

    2. Exchange students and CEMS students

    3. Other Aalto students


    Teaching Period:

    2020-2021 Autumn II

    2021-2022 Autumn II


    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=ISM-C1004


    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.