Introduction to Artificial Intelligence

Lecturers

Details

Course type
Lectures
Credits
5 CP
Term
Summer Term 2023
E-Learning
moodle course available

Dates

Lecture
Takes place every week on Friday from 10:15 to 11:45 in room HGD 20.
First appointment is on 14.04.2023
Last appointment is on 14.07.2023
Lecture
Takes place every week on Friday from 12:15 to 13:45 in room HGD 20.
First appointment is on 14.04.2023
Last appointment is on 14.07.2023
Examination
Takes place on 01.08.2023 from 11:00 to 12:40 in room computer pool MABF 01/556.
Examination
Takes place on 21.09.2023 from 11:00 to 12:40 in room computer pools 1 & 2 in ID, see https://etit.ruhr-uni-bochum.de/fakultaet/zentrale-einrichtungen/cip/.

Lecturers: Laurenz Wiskott, Sen Cheng, Tobias Glasmachers, Gregor Schöner, Maribel Acosta, Asja Fischer, Christian Straßer (sorry, for technical reasons, we could not display him above), Robert Schmidt

Enrollment: Students from the RUB Bachelor study programs (Applied) Computer Science simply enroll in the Moodle course and participate. Students from the TU Dortmund Master study program Data Science contact their coordinator Daniel Horn. Others send an email to Laurenz Wiskott. You might also have to enroll for this course in your examination office, but this is something you'll have to figure out yourself.

Credits: 5 CP (3 CP for Master-students from technical study programs with heavy computer science and/or math components; 0 CP for (Applied) Computer Science Master-students; technical study programs include IT-Security, Maschinenbau, Data Science (TU Do), and Automation & Robotics (TU Do); non-technical study programs include Biology and Chemistry)

Workload: 150 h (90 h for Master-students from technical study programs)

Semester: second semester Bachelor

Cycle (Turnus): each SS

Duration (Dauer): 1 semester

Contact time (Kontaktzeit): 4 SWS (60 h)

Self studies (Selbststudium): 90 h

Group size (Gruppengröße): ca 300

Language: English.

Requirements: Basic knowledge of calculus and linear algebra.

Learning outcomes (Lernziele): After successful completion of this course, students will be able to

  • summarize a number of fundamental methods in artificial intelligence,
  • explain their mathematical basis and algorithmic nature,
  • apply them to simple problems,
  • decide which methods are suitable for which problems, and
  • communicate about the above aspects in English.

Content (Inhalt): This course gives an overview over representative methods in artificial intelligence: formal logic and reasoning, classical methods of AI, probabilistic reasoning, machine learning, deep neural networks, computational neuroscience, neural dynamics, perception, natural language processing, and robotics.

Teaching format (Lehrformen): This course is given with the flipped/inverted classroom concept. The students work through online material beforehand and this will then be deepened in the contact sessions, which will be used for an interactive exchange between students and with the lecturer in a flexible format.

Exam (Prüfungsformen) (updated 2023-06-21): The course is concluded with a digital written exam for 90 minutes within a 100 minutes time slot. We offer two dates in the semester of the course and none in the next semester. You are free to pick either of the two dates, but if you pick the second and you fail, the next opportunity to retry the exam is only about one year later.

The exam will be in presence, and it will be a closed book exam, thus you are not allowed to use any tools.

Registration for the exam with us happens at the end of the course. In addition to being registered for the regular Moodle course you have to register for the Exam Moodle, and then you simply take the exam. You might also have to register for this exam in your examination office, but this is something you'll have to figure out yourself. Registering with us and with the examination office are independent of each other. If possible we will report your grade to the examination office in any case, whether you have registered there or not. There are no prerequisits for the exam, like 50% points in tutorials or the like.

A mock exam will be available towards the end of the course. It will be shorter than the final exam, but it will contain at least one question by every teacher. The main purpose is to give you a good impression of the style of the exam and therefore facilitate exam preparation.

Condition for granting the credit points (Voraussetzungen für die Vergabe von Kreditpunkten) (updated 2023-07-25): You need at least 50 out of 100 points in the final exam. These are not directly the points of the quiz questions in the exam. The 1st and 2nd exam have a chance level C if you would do pure guessing and a maximal number of points M if you answer everything correctly. The default mapping from exam points to the 100  point grading scheme is 100*(P-C)/(M-C), where P is your individual number of points you have got in the exam. So, with pure guessing, i.e. P=C, you would get 0 points on average and with perfect answers, i.e. P=M, you get 100 points.

About the INI

The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.

Contact

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210

sekretariat@ini.rub.de
www.ini.rub.de