Advanced Predictive Analytics

Exam number: 6810

Semester: from 1st semester

Duration of the module: One semester

Form of the module (i.e. obligatory, elective etc.): Elective

Frequency of module offer: Summer semester 2019

Prerequisites: tba

Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.

Person responsible for module: Prof. Dr. Sven Müller

Name of the professor: Prof. Dr. Sven Müller

Language of teaching: English

ECTS-Credits (based on the workload): 6

Workload and its composition (self-study, contact time):
Contact time (Lecture, tutorial etc.): 30 h; self-study: 150 h

Contact hours (per week in semester): 2

Methods and duration of examination:
tba

Emphasis of the grade for the final grade: Please check regulations of the study programme

Aim of the module (expected learning outcomes and competencies to be acquired):
tba

Contents of the module:
This course continues the learning of discrete choice models introduced in the course "Predictive Analytics". In particular, we focus on models and algorithms that improve the predictive quality of classic discrete choice models. For example, nested, cross-nested logit models, MEV models, probit models, and mixed logit. Further, we discuss how attitudes, perceptions etc impact the choice behavior of individuals and how we can account for these in modern (hybrid) choice models.

Teaching and learning methods:
tba

Literature (compulsory reading, recommended literature):
tba

Further information:
Registration in Moodle Viadrina required.