Moses - Applied Artificial Intelligence Project

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Module / Version:
#40889 / #2

Validity:
Seit WiSe 2022/23

Default display language:
English

Module title:
Applied Artificial Intelligence Project

Credits:
9

Responsible person:
Albayrak, Sahin

Grading:
benotet

Type of exam:
Portfolioprüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Wirtschaftsinformatik und Quantitative Methoden

Area of expertise:
34361200 FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT)

Prüfungsausschuss:
No information

Kontakt

Office:
TEL 14

Contact person:
Xu, Yuan

E-mail address:
sahin.albayrak@tu-berlin.de

Website:

https://www.aot.tu-berlin.de/index.php?id=2889

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

In this module, the students learn to apply general programming techniques as well as artificial intelligence methods in a competitive setting. Here, the application of artificial intelligence comprises symbolic as well as sub-symbolic approaches. The competitive environment is given through the participation in external competitions or course internal competitions amongst the student groups depending on the particular semester schedule. Particularly, students will explore the challenges of autonomous driving in a small scale flavor using simulation environments as well as small scale cars equipped with all relevant sensor perception. Specific applications encompass obstacle avoidance, autonomous racing, cooperation maneuver like convoying, prediction of others, multi-agent teamwork.

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Applied Artificial Intelligence Project	PJ	0435 L 797	WiSe/SoSe	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, basic knowledge about robotics or automation, fundamental knowledge in artificial intelligence (symbolic and/or sub-symbolic)

Mandatory requirements for the module test application:

No information

Module completion

Grading

graded

Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt

Language

German

Test elements

Name	Points	Categorie	Duration/Extent
Design	25	written	2 weeks / 10 pages (approx.)
Evaluation and documentation	25	written	2 weeks / 10 pages (approx.)
Final Presentation and Review	20	oral	90 min.
Implementation and Test	30	practical	5 weeks

Grading scale

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl	1.0	1.3	1.7	2.0	2.3	2.7	3.0	3.3	3.7	4.0
100.0pt	95.0pt	90.0pt	85.0pt	80.0pt	75.0pt	70.0pt	65.0pt	60.0pt	55.0pt	50.0pt

Test description (Module completion)

No information

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Winter- und Sommersemester.

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 literature
No recommended literature given

Assigned Degree Programs

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

This module is used in the following Degree Programs (new System):

Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
Computer Engineering (M. Sc.)	1	6	WiSe 2022/23	WiSe 2023/24
Computer Science (Informatik) (M. Sc.)	1	6	WiSe 2022/23	WiSe 2023/24
Elektrotechnik (M. Sc.)	1	3	WiSe 2022/23	WiSe 2023/24
ICT Innovation (M. Sc.)	1	6	WiSe 2022/23	WiSe 2023/24
Information Systems Management (Wirtschaftsinformatik) (M. Sc.)	1	3	WiSe 2022/23	WiSe 2023/24
Medieninformatik (M. Sc.)	1	2	WiSe 2022/23	SoSe 2023
Medientechnik (M. Sc.)	1	2	WiSe 2023/24	WiSe 2023/24
Physikalische Ingenieurwissenschaft (M. Sc.)	2	6	WiSe 2022/23	WiSe 2023/24
Wirtschaftsingenieurwesen (M. Sc.)	1	3	WiSe 2022/23	WiSe 2023/24

Miscellaneous

No information

Applied Artificial Intelligence Project

Zugehörigkeit

Kontakt

Learning Outcomes

Content

Module Components

Pflichtgruppe:

Workload and Credit Points

Applied Artificial Intelligence Project (PJ):

Description of Teaching and Learning Methods

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Mandatory requirements for the module test application:

Module completion

Grading

Type of exam

Type of portfolio examination

Language

Test elements

Grading scale

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Test description (Module completion)

Duration of the Module

Maximum Number of Participants

Registration Procedures

Recommended reading, Lecture notes

Lecture notes

Electronical lecture notes

Literature

Assigned Degree Programs

This module is used in the following Degree Programs (new System):

Miscellaneous