Applications of AI (5op)

Arviointiasteikko

H-5

Sisällön jaksotus

Part 1: Natural Language Processing NLP that covers 50% of the course is based on the AWS academy online course for NLP Natural Language Processing that includes the following modules:
Module 1 - Welcome to AWS Academy NLP
Module 2 - Introduction to Natural Language Processing (NLP)
Module 3 - Processing Text for NLP
Module 4 - Implementing Sentiment Analysis
Module 5 - Introducing Information Extraction
Module 6 - Introducing Topic Modeling
Module 7 - Working with Languages
Module 8 - Working with Generative AI
Module 9 - Course Wrap-up

Part 2: Image Processing

Tavoitteet

After completing the course, the student can:
- describe what kind of AI applications are available
- describe how AI based applications can be developed
- develop applications using AI

Sisältö

Actual content is decided during the course implementation phase.
The contents vary every year.

Oppimateriaalit

Material available via the learning environment (ITS).

Opetusmenetelmät

Weekly face-to-face meetings with lecture teaching and small group work
- Learning by doing and experimenting (exercise tasks, project work, information search)
- Small group work and peer learning
- Self-study material
- Teacher guidance and examples

Tenttien ajankohdat ja uusintamahdollisuudet

No exam

Pedagogiset toimintatavat ja kestävä kehitys

This course applies pedagogic methods like flipped learning, hands-on labs, and problem-based projects using platforms such as AWS Academy. These methods help students build real-world skills in deploying, managing, and securing scalable cloud solutions. Peer collaboration and continuous feedback support active engagement and reflection.

The course aligns with sustainable development goals by addressing energy-efficient computing, digital access and inclusion, and industry innovation. Students explore how cloud solutions can reduce hardware waste, optimize resource use, and support remote, low-energy infrastructure. Projects may include deploying serverless applications or calculating the carbon footprint of various cloud architectures.

This integrated approach prepares students to design sustainable, scalable, and socially responsible cloud solutions.

Toteutuksen valinnaiset suoritustavat

None.

Opiskelijan ajankäyttö ja kuormitus

Contact hours:
- Week 3: Course Introduction 2h
Part 1: NLP - Self paced AWS academy Module (3h/week): 6 x 3h = 18h (Ali Khan)
- Weeks 4 - 9 & Week 16: NLP - Total 6 weeks
- Week 8 - Winter Holidays
- Week 16 Final Project Presentations NLP
Part 2: Image Applications - Theory & practice (3h/week): 6 x 3h = 18h (Pertti Ranttila)
- Weeks 10 - 15 : Image Applications - Total 6 weeks
Total contact hours: 40 hours

Independent study and homework: about 90 h

Total: approximately: 130 hours

Arviointimenetelmät ja arvioinnin perusteet

For NLP Part:
- AWS Academy Course labs: 40 points
- Project: 10 points

For Image Applications Part:
- 50 points from practical exercises in class room and home work

It is mandatory to get at least 50% points in each of the above parts (NLP and Image Applications) to pass this course.

Hylätty (0)

Under 50

Arviointikriteerit, tyydyttävä (1-2)

50 points -> 1
60 points -> 2

Arviointikriteerit, hyvä (3-4)

70 points -> 3
80 points -> 4

Arviointikriteerit, kiitettävä (5)

90 points -> 5

Lisätiedot

ItsLearning