In this module, basic paradigms and current challenges in working with data will be discussed, especially data security and the handling of large amounts of data.
Lernziel
Participants learn about some important computer science concepts necessary for data science. They understand some of these concepts in detail and see the mathematics behind them.
Inhalt
Participants will get an introduction to key computer science concepts underlying current and upcoming technology. The module covers cryptography, distributed ledger technology, machine learning and artificial intelligence, as well as algorithms for big data. Each concept will be discussed in two different ways: (i) a hands-on introduction that allows participants to gain a technical understanding of key ideas. This is supported by simple and concrete examples as well as programming assignments; (ii) a context part that explains the challenges and limitations encountered in practical applications.
Leistungskontrolle
Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Repetition ohne erneute Belegung der Lerneinheit möglich.
Zusatzinformation zum Prüfungsmodus
Written exam, 90 minutes
During the course, we will hand out homeworks. Solutions will be graded, and the grades will account for 20% of the final grade. Homeworks can be discussed with colleagues, but we expect an independent writeup. Homeworks that are not being submitted will receive a grade of 1.
Lernmaterialien
Keine öffentlichen Lernmaterialien verfügbar.
Es werden nur die öffentlichen Lernmaterialien aufgeführt.
Gruppen
Keine Informationen zu Gruppen vorhanden.
Einschränkungen
Vorrang
Die Belegung der Lerneinheit ist nur durch die primäre Zielgruppe möglich
Primäre Zielgruppe
MAS ETH in Applied Technology (247000)
CAS ETH in Applied Information Technology (265000)
Leistungskontrolle als Semesterkurs