Introduction to Data Engineering and AI Technologies (5 op)

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