Trends and Concepts Exercise: Developing In-Memory Applications (Sommersemester 2016)

Lecturer: Dr. Matthias Uflacker
Tutors: Christian Schwarz Martin Boissier

General Information

• Weekly Hours: 4
• Credits: 6
• Graded: yes
• Enrolment Deadline: 22.04.2016
• Teaching Form: Project seminar
• Enrolment Type: Compulsory Elective Module

Programs, Module Groups & Modules

Description

Latest: The mid-term presentation will take place on 24.05.2016

The Seminar

Within the seminar, small groups of students will define and develop enterprise applications leveraging in-memory database technology. Each group will have access to an in-memory database with real-world and simulated data. Using that data set the groups are free to choose what approach they will eventually implement in order to build the best possible solution for their individual challenge.

This year the students will be challenged with the detection of fraud on a large scale, real world enterprise dataset of a platform for online vehicle markets. The students will get guidance on machine learning classification and regression techniques. These will be used in the project.

During the seminar, the student teams will be supervised in individual sessions.

Literature

• Download of result validation API: T-002/tacex_2016 on github

Examination

Part	Valuation in %	Type
Presentations (Mid-term / Final)	30 (10 / 20)	Personal grade
Results	30	Personal grade
Documentation (+ Screencast)	30	Personal grade
General participation in the seminar	10	Personal grade

 

Dates

• Seminar Introduction: 12.04.2015 -  3:15 PM (House D, E.9/10)
  
• First Meeting and Use-case presentation: 19.04.2015 - 3:15 PM (House D, E.9/10)
• Topic Deep Dive: 26.04.2016
• Mid-Term Presentation: 24.05.2016 - 4 PM (Villa, V2.16)
• Final Presentation: 12.07.2016 (Villa, V2.16)
• Screencast and Documentation: 15.08.2016 (tbd)

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