Navigation To modulepage
Display language

Applied Artificial Intelligence Project

9 LP

English

#40889 / #1

Seit SS 2018

Fakultät IV

TEL 14

Institut für Wirtschaftsinformatik und Quantitative Methoden

34361200 FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT)

Albayrak, Sahin

Fricke, Stefan

sahin.albayrak@tu-berlin.de

POS-Nummer PORD-Nummer Modultitel
2347963 39678 Applied Artificial Intelligence Project

Learning Outcomes

After successfully finishing this module, the participating students have • well-founded knowledge in an application domain • hands-on experiences in applying methods from the field of Artificial Intelligence to challenging problems of the future society • improved their capacity for teamwork and competence in project management • improved presentation and writing skills

Content

This module addresses challenges in one of the following domains with accompanying topics, such as: eGovernment: exploitation of Linked Open Data, application of enterprise management systems in administration offices, analysis of Big Data for the improvement of public services. Energy: energy patterns in households or the operation of smart micro grids. Industry 4.0, in combination with cyberphysical systems and the Internet of Things. Health care and Abient Assisted Living: diagnosis, surveillance, and information services based on sensor data or the analysis of social media streams. Logistics and Transport: traffic flow analysis and forecasting, and control; car sharing; intermodal public transport routing.

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course Name Type Number Cycle Language SWS
Applied Artificial Intelligence Project PJ 0435 L 797 WS/SS No information 4

Workload and Credit Points

Applied Artificial Intelligence Project (PJ):

Workload description Multiplier Hours Total
Attendance 15.0 4.0h 60.0h
Pre/post processing 15.0 14.0h 210.0h
270.0h (~9 LP)
The Workload of the module sums up to 270.0 Hours. Therefore the module contains 9 Credits.

Description of Teaching and Learning Methods

Project work within small groups, weekly project meetings, milestones, requirements specification, implementation, evaluation, documentation, presentation of results.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Fundamental programming experience

Mandatory requirements for the module test application:

No information

Module completion

Grading:

graded

Type of exam:

Portfolio examination

Language:

German

Typ of portfolio examination

100 points in total

Test elements

Name Points Categorie Duration/Extent
Final Presentation 20 oral 1 hour
Milestone Presentation 10 oral 1 hour
Project Results 50 practical 13 weeks
Requirements Specification 10 written approx. 10 pages
Status Reports 10 flexible 0.5 hours per week

Grading scale

1.01.31.72.02.32.73.03.33.74.0
95.090.085.080.075.070.065.060.055.050.0

Test description (Module completion)

No information

Duration of the Module

This module can be completed in one semester.

Maximum Number of Participants

The maximum capacity of students is 20.

Registration Procedures

QISPOS registration as well as according to the specific examination regulations (Prüfungsordnung). Additionally, the registration on the ISIS course page is required prior to the start of the semester.

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable

Electronical lecture notes

Availability:  unavailable

Literature

Recommended literature
No recommended literature given.

Assigned Degree Programs

This module is used in the following modulelists:

Miscellaneous

No information