Basics of AI (5 cr)
Code: BIG8TN001-3001
Basic information of implementation
- Enrollment
- 18.03.2019 - 29.03.2019
- Enrolment for the implementation has ended.
- Timing
- 25.03.2019 - 31.07.2019
- Implementation has ended.
- ECTS Credits
- 5 cr
- Campus
- Pasila Campus
- Teaching languages
- English
- Seats
- 15 - 26
- Degree programmes
- HETI Degree Programme in Business Information Technology
- Teachers
- Lili Aunimo
- Heli Lankinen
- Course
- BIG8TN001
Evaluation scale
H-5
Schedule
Mon 10.4. Pre-assignment (Assignment 1) published
Mon 24.4.: DL for pre-assignment (Assignment 1)
Thu 2.5. notification of acceptance and beginning of individual work
Contact lessons on Mondays and Wednesdays between 20.5. and 5.6. at 16.30 -19.30
Mon 20.5., Career Night, place: Microsoft premises in Keilaniemi
Wed 22.5.: Introduction, project work description and assignment 2 is given
Monday 27.5. project teams are formed
Wed 29.5.: Assignment 2 based discussions , hands-on work, guidance
Mon 3.6. hands-on work, guidance
Wed 5.6. project work presentations
Tue 11.6. Final project work is due
Intro
In this course, we explore artificial intelligence (AI). What does artificial intelligence mean and what does intelligence mean? We neglect the coding part of the course since the focus of the course is to answer these questions
Materials
Future Computed: https://news.microsoft.com/uploads/2018/01/The-Future-Computed.pdf
Artificial Intelligence for Dummies /Mueller & Massaron (e-book)
Microsoft: DAT207x Analyzing and Visualizing Data with Power BI
Microsoft: Dat263x Introduction to Artificial Intelligence (AI)
Other materials given by the teachers during the course.
Teaching methods and instruction
Contact lessons 6 X 4h = 24 h
Independent study and teamwork 110 h
Self-assessment of learning assignment (1 h)
Working life connections
The course is implemented in cooperation with Microsoft. There is a career night where recruiting companies introduce themselves and tell about their recruiting needs and projects in the field of artificial intelligence. Students have the possibility to apply for a work placement or a thesis work position in these companies.
Internationality
The course materials are international.
Learning assignments
Learning assignment 1: Introduction to AI
Learning assignment 2: Basic concepts and methods of AI
Learning assignment 3: Analyzing and visualizing data with Power BI
Learning assignment 4: Artificial Intelligence Lab.
Project work done in teams.
Self-assessment of learning assignment.
The self- assessment of learning assignment is completed online. The assignment serves as an assessment of your learning and as course feedback. The assignment does not affect the grade.
Assessment methods
Project work in team 40%
Individual assignments (pre-assignment and three other) 50%
Activeness during contact lessons 10%