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Regular version of the site

Geomarketing

2019/2020
Academic Year
ENG
Instruction in English
3
ECTS credits
Course type:
Elective course
When:
3 year, 3 module

Course Syllabus

Abstract

The course introduces students to the geomarketing discipline. they will study geomarketing problems and methods as they are used in the real life retail. Students will rehearse econometrics and data analysis with software and basic programming with Python or R.
Learning Objectives

Learning Objectives

  • Getting familiar with geospatial informatics in general.
  • Learn basic geometry processing.
  • Study how to make judgement whether places offerend for rent are worth it.
Expected Learning Outcomes

Expected Learning Outcomes

  • Comprehensive knowledge of econometrics.
  • Basics knowledge of data analysis.
  • Being able to apply machine learning algorithms to data and spatial data.
  • Being able to process geospatial data.
  • Being able to make predictions with state-of-the-art software algorithms or making the predictive analysis.
Course Contents

Course Contents

  • Basics of Geoinformatics
  • Predictions Algorithms
  • General AI Topics
    - Applicability - Case Studies - Hype and Failed Promises
  • Urban Problems and Retail
    - Transport Problems - Incomes, Inequality, Gentrification - Socialization in Cities and New Demands
Assessment Elements

Assessment Elements

  • non-blocking First test
  • non-blocking First assignment
  • non-blocking Second assignment
  • non-blocking Second test
Interim Assessment

Interim Assessment

  • Interim assessment (3 module)
    0.28 * First assignment + 0.16 * First test + 0.28 * Second assignment + 0.28 * Second test
Bibliography

Bibliography

Recommended Core Bibliography

  • Kumar, A. (2016). Learning Predictive Analytics with Python. Birmingham: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1171944

Recommended Additional Bibliography

  • de Smith, M., Goodchild, M., & Longley, P. (2009). Geospatial analysis: a Comprehensive Guide to Principles, Techniques and Software Tools. United Kingdom, Europe: Troubador Ltd. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.B70B9802
  • Mills, J. W. (2008). Geospatial Analysis: A Comprehensive Guide to Principles, Techniques, and Software Tools, Second Edition - by Michael J. de Smith, Michael F. Goodchild, and Paul A. Longley. Transactions in GIS, 12(5), 645–647. https://doi.org/10.1111/j.1467-9671.2008.01122.x