650.000 (22W) Fundamentals of Artificial Intelligence and Cybersecurity
Überblick
Weitere Informationen zum Lehrbetrieb vor Ort finden Sie unter: https://www.aau.at/corona.
- Lehrende/r
- LV-Titel englisch Fundamentals of Artificial Intelligence and Cybersecurity
- LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
- LV-Modell Blended-Learning-Lehrveranstaltung
- Online-Anteil 80%
- Semesterstunde/n 3.0
- ECTS-Anrechnungspunkte 4.0
- Anmeldungen 21 (30 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 04.10.2022
- eLearning zum Moodle-Kurs
Zeit und Ort
LV-Beschreibung
Intendierte Lernergebnisse
The aim of this course is to provide the students with the basic knowledge of mathematics, statistics and probability theory that will be required to follow the different courses on cybersecurity and AI.
Lehrmethodik inkl. Einsatz von eLearning-Tools
Face-to-face lectures with online stream combined with moodle content (Information about them is on the course's moodle page.)
Depending on the participation possibilities, lecture mode can change (online, hybrid).
Inhalt/e
The topics included in this course are: discrete probability distributions, conditional distribution independence, random variables, moments of random variables (additional contents if there is time), vector and matrix arithmetic, properties of inverse and orthogonal matrices, properties of eigenvalues and eigenvectors, properties of singular value decomposition.
Additionally, the course will cover basic notions of Computer Science, in particular computability and complexity, formal languages and automata.
Literatur
References to the recommended books and literature necessary for this course will be given on the course moodle page.
Prüfungsinformationen
Prüfungsmethode/n
Performance of the students will be evaluated through moodle quizzes. The details of the quizzes including their schedule and other relevant information will be announced on course moodle page.
Prüfungsinhalt/e
The topics of the quizzes will be same as the topics covered in the lectures.
Beurteilungskriterien/-maßstäbe
Written online quizzes. Dates are announced in Moodle.
The overall evaluation of the course is a combination of three evaluations, one for the contents on stochastics, one for the contents on linear algebra, and one for the contents on computer science. Each of the three parts is worth 16 points, in total you can get up to 48 points. To pass the whole course, you need to pass all three evaluations individually. This means that you need to collect at least 8 points respectively for every individual part. Given that you satisfy this constraint, the final grade is determined by the total sum of points over all three evaluations according to the following grading table:
| Grade 1 ("Sehr gut"): | >= 42 |
| Grade 2 ("Gut"): | >= 36 |
| Grade 3 ("Befriedigend"): | >= 30 |
| Grade 4 ("Genügend"): | >= 24 |
Beurteilungsschema
Note BenotungsschemaPosition im Curriculum
- Masterstudium Artificial Intelligence and Cybersecurity
(SKZ: 993, Version: 20W.1)
-
Fach: Foundations of Artificial Intelligence and Cybersecurity
(Pflichtfach)
-
1.1 Fundamentals of Artificial Intelligence and Cybersecurity (
0.0h VC / 4.0 ECTS)
- 650.000 Fundamentals of Artificial Intelligence and Cybersecurity (3.0h VC / 4.0 ECTS) Absolvierung im 1. Semester empfohlen
-
1.1 Fundamentals of Artificial Intelligence and Cybersecurity (
0.0h VC / 4.0 ECTS)
-
Fach: Foundations of Artificial Intelligence and Cybersecurity
(Pflichtfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
-
Wintersemester 2024/25
- 650.000 VC Fundamentals of Artificial Intelligence and Cybersecurity (3.0h / 4.0ECTS)
-
Wintersemester 2023/24
- 650.000 VC Fundamentals of Artificial Intelligence and Cybersecurity (3.0h / 4.0ECTS)
-
Wintersemester 2021/22
- 650.000 VC Fundamentals of Artificial Intelligence and Cybersecurity (3.0h / 4.0ECTS)
-
Wintersemester 2020/21
- 650.000 VC Fundamentals of Artificial Intelligence and Cybersecurity (3.0h / 4.0ECTS)