Study Guide

Learning outcomes

The student is able to:
• understand what is AI and how it can affect business
• recognize opportunities of AI in different domains
• is able to analyze and visualize data
• knows the basic statistical methods used in data analysis
• knows how to use software to perform data analysis
• knows how to apply some basic methods used in AI
• knows trends in AI
• can recognize ethical challenges related to applying AI in business

Teaching methods

Lectures and workshops 6 X 4h = 24 h
Independent study and teamwork 110 h
Self-assessment of learning assignment (1 h)
Course Conent
• definition of AI and basic concepts related to it
• business cases where AI is used
• methods and software for data analysis and visualization
• basics of statistical data analysis methods
• application of AI methods in a project work
• recent trends in AI
• ethical issues in AI

Location and time

Teacher(s) responsible
Lili Aunimo, Pasila, Haaga-Helia
Heli Lankinen, Pasila, Haaga-Helia
Lassi Tissari, Leppävaara, Laurea

Learning materials and recommended literature

TBA later

Co-operation with working life and/or RDI

-

Important dates

Mon 10.4. Pre-assignment published
Mon 24.4..: DL for pre-assignment
Thu 2.5. notification of acceptance and beginning of individual work
Weeks 21 - 23 classes at 16.30 -19.30
Week 21:
- Monday 20.5.2019, at MS: Career Night
- Wednesday 22.5.2019: Introduction, project work description and assignment 2 is given
Week 22:
- Monday 27.5., project teams
- Wednesday 29.5.: Assignment 2 based discussions
Week 23:
- Monday 3.6.2019
- Wednesday 5.6.2019 project work presentations
Week 24
- Tuesday 11.6. Final project work is due

Forms of internationality

-

Students workload

Lectures and workshops 6 X 4h = 24 h
Independent study and teamwork 110 h
Self-assessment of learning assignment (1 h)

Further information for students

This is a course planned in co-operation with Laurea, Microsoft, and partner companies, who are keen to grow and develop new AI talent. The focus is on the practical application of AI concepts, tools and methods to address business needs and improve business processes. The course is more about how companies are using AI solutions in their operations and less about AI as a science. Some of the AI tools covered in the course are based on Microsoft’s technologies. Representatives of Microsoft’s partner companies will participate as guest lecturers. A Career Night event on May 20th will be organized at Microsoft premises at Keilalahti with the partner companies, where you will have a chance to negotiate AI related internships and thesis topics with the companies.

Grading scale

H-5

Evaluation methods and criteria

Project work in team 40%
Individual assignments (pre-assignment and three other) 50%
Activeness at lectures and workshops 10%
The self- assessment of learning assignment does not impact your grade. The assignment is the same for all courses/modules and your answers will be used also for course/module development.
The assignment is completed online

Evaluation criteria, satisfactory (1-2)

The student can identity, list and combine the main AI concepts.
With great difficulty and under strict supervision, the student can partly apply AI methods to a business case at a beginner’s level.
With great difficulty and under strict supervision, the student can partly work on a business case in a team. S/he can poorly apply problem identification, analysis and solving to AI projects. S/he can use software on a limited level.

Evaluation criteria, good (3-4)

The student can describe the relevant AI and apply them to new contexts. The student can link the key theoretical concepts to the practical task to present the big picture.
The student can apply AI methods in a business case at a beginner’s level.
The student can work on an AI business case in a team. S/he can apply problem identification, analysis and solving to AI projects. S/he can use AI software and methods.

Evaluation criteria, excellent (5)

The student uses and combines different AI methods in his/her own business cases. Student is aware of other views of the knowledge. His/her use of theory and specific terminology is very accurate.
S/he can compare different AI methods and viewpoints into AI.
The student can apply appropriate AI methods to a business case at a basic professional level.
The student can work professionally on an AI business case in a team. S/he can fully apply problem identification, analysis and solving to AI projects. S/he can use AI software and methods on a basic professional level.