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: 26.10.2020 - 10.12.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Juuso Liesiö
Teacher in charge (applies in this implementation): Juuso Liesiö
Contact information for the course (valid 25.09.2020-21.12.2112):
Prof. Juuso Liesiö (juuso.liesio(at)aalto.fi)
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
Valid 01.08.2020-31.07.2022:
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 01.08.2020-31.07.2022:
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 01.08.2020-31.07.2022:
Contact teaching 36h (no mandatory attendance), individual work 121h, exam 3h. Total 160h (ECTS).
Applies in this implementation:
Online sessions 36h
Class preparation 12h
Assignments 102h
Preparing for the exam 7h
Exam 3h
DETAILS
Study Material
Valid 01.08.2020-31.07.2022:
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
Valid 01.08.2020-31.07.2022:
27C01000 Business Decisions 1
Prerequisites
Valid 01.08.2020-31.07.2022:
Courses "30A01100 Introduction to Business Analytics" and "30A02000 Introduction to Statistics” (or equivalent skills).
FURTHER INFORMATION
Details on the schedule
Applies in this implementation:
See course front page
- Teacher: Liesiö Juuso
- Teacher: Raita Tommi
- Teacher: Vilkkumaa Eeva
- Teacher: Xu Peng