MLOpsLaajuus (5 op)
Tunnus: MS00CN45
Laajuus
5 op
Osaamistavoitteet
After completing the course, the students can
- describe and understand how MLOps projects operate
Sisältö
- Process and tools for Machine Learning Engineering for Production (MLOps)
Ilmoittautumisaika
02.12.2024 - 31.12.2024
Ajoitus
01.01.2025 - 31.07.2025
Opintopistemäärä
5 op
Toteutustapa
Lähiopetus
Toimipiste
Kupittaan kampus
Opetuskielet
- Suomi
- Englanti
Paikat
10 - 30
Koulutus
- Insinööri (ylempi AMK), Data Engineering and AI
- Tradenomi (ylempi AMK), Data Engineering and AI
Opettaja
- Jussi Salmi
Ryhmät
-
YINTES24Master of Engineering, Interactive Technologies
-
YINTBS24Master of Business Administration, Interactive Technologies
-
YDATIS24Insinööri (ylempi AMK), Data Engineering and AI
-
YDATTS24Tradenomi (ylempi AMK), Data Engineering and AI
Tavoitteet
After completing the course, the students can
- describe and understand how MLOps projects operate
Sisältö
- Process and tools for Machine Learning Engineering for Production (MLOps)
Oppimateriaalit
Teacher provided lecture material
Supporting public online material
Teacher provided virtual machines
All needed material (or at least a link to them) will be available in itslearning.
Itslearning and contact classes are the main communication channels used on this course.
The student is required to have a computer capable of running a simple Ubuntu virtual machine.
Opetusmenetelmät
Contact learning, practical assignments, independent study
Opiskelijan ajankäyttö ja kuormitus
Contact hours 16 h
Inpendent studying 119h, including:
- Studying the course material
- Completing assignments
- Project
Sisällön jaksotus
After completing the course, the students can
- describe and understand how MLOps projects operate
Process and tools for Machine Learning Engineering for Production (MLOps)
Scheduling:Chosen topics from MLops, Dataops and Devops for artificial intelligence and data engineering students.
Arviointiasteikko
H-5
Arviointimenetelmät ja arvioinnin perusteet
Assignments returned throughout the course
Small project at the end of the course
Ilmoittautumisaika
02.12.2023 - 15.01.2024
Ajoitus
15.01.2024 - 30.04.2024
Opintopistemäärä
5 op
Toteutustapa
Lähiopetus
Yksikkö
Tekniikka ja liiketoiminta
Opetuskielet
- Suomi
- Englanti
Koulutus
- Insinööri (ylempi AMK), Data Engineering and AI
- Tradenomi (ylempi AMK), Data Engineering and AI
Opettaja
- Tommi Tuomola
Ryhmät
-
YDATIS23Insinööri (ylempi AMK), Data Engineering and AI
-
YDATTS23Tradenomi (ylempi AMK), Data Engineering and AI
Tavoitteet
After completing the course, the students can
- describe and understand how MLOps projects operate
Sisältö
- Process and tools for Machine Learning Engineering for Production (MLOps)
Oppimateriaalit
Teacher provided lecture material
Supporting public online material
Teacher provided virtual machines
All needed material (or at least a link to them) will be available in itslearning.
Itslearning and contact classes are the main communication channels used on this course.
The student is required to have a computer capable of running a simple Ubuntu virtual machine.
Opetusmenetelmät
Contact learning, practical assignments, independent study
Opiskelijan ajankäyttö ja kuormitus
Contact hours 16 h
Inpendent studying 119h, including:
- Studying the course material
- Completing assignments
- Project
Sisällön jaksotus
After completing the course, the students can
- describe and understand how MLOps projects operate
Process and tools for Machine Learning Engineering for Production (MLOps)
Scheduling:Chosen topics from MLops, Dataops and Devops for artificial intelligence and data engineering students.
Arviointiasteikko
H-5
Arviointimenetelmät ja arvioinnin perusteet
Assignments returned throughout the course
Small project at the end of the course