Introduction to Data Engineering and AI Technologies (5 op)
Toteutuksen tunnus: MS00CN43-3001
Toteutuksen perustiedot
- Ilmoittautumisaika
- 17.05.2023 - 11.09.2023
- Ilmoittautuminen toteutukselle on päättynyt.
- Ajoitus
- 01.09.2023 - 15.12.2023
- Toteutus on päättynyt.
- Opintopistemäärä
- 5 op
- Lähiosuus
- 5 op
- Toteutustapa
- Lähiopetus
- Yksikkö
- Tekniikka ja liiketoiminta
- Opetuskielet
- englanti
- Paikat
- 10 - 35
- Koulutus
- Insinööri (ylempi AMK), Data Engineering and AI
- Tradenomi (ylempi AMK), Data Engineering and AI
- Opettajat
- Golnaz Sahebi
- Ryhmät
-
YDATIS23Insinööri (ylempi AMK), Data Engineering and AI
-
YDATTS23Tradenomi (ylempi AMK), Data Engineering and AI
- Opintojakso
- MS00CN43
Arviointiasteikko
H-5
Sisällön jaksotus
Course Outline and Schedule:
Week 37: Introduction to the Course and Data Preprocessing:
• Project overview and requisites
• Initiation of project's initial phase: Data preprocessing and visualization (assignment 1)
Week 41: Machine Learning I
• Students' presentations showcasing outputs and implementation of the first assignment
• Commencement of phase two: Supervised and unsupervised learning (assignment 2)
Week 45: Machine Learning II
• Students' presentations showcasing outputs and implementation of the second assignment
• Tuning and optimizing your Machine Learning algorithms (assignment 3)
Tavoitteet
After completing the course, the student can:
- describe basic concepts and processes related to Data Engineering and AI
Sisältö
- Data Engineering process
- Basics of AI
- Fields and evolution of AI
- Big data
- Basics of Machine Learning
Oppimateriaalit
Material will be available via the learning environment (ITS) and our institution's eBook Central database.
Tenttien ajankohdat ja uusintamahdollisuudet
No exam
Opiskelijan ajankäyttö ja kuormitus
Contact hours:
- 4 times 3h theory and practice: 4 x 4h = 12 hours
Assignments for the final project: approximately 118 hours
Total: approximately: 130 hours
Arviointimenetelmät ja arvioinnin perusteet
The course is graded on a scale of 0-5.
*
In order to receive an approved performance and pass the course, the student must receive an acceptable mark for the three assignments.
*
You can get at most 40, 30, and 30 points for each phase of the project (assignments 1-3). You can therefore get a maximum of 100 points from all phases of the project.
Hylätty (0)
Less than 50 points in assignments not passed.
Arviointikriteerit, tyydyttävä (1-2)
50 - 65 points from the total points of the assignments
Arviointikriteerit, hyvä (3-4)
66 - 80 points from the total points of the assignments
Arviointikriteerit, kiitettävä (5)
81- 100 points from the total points of the assignments