Artificial IntelligenceLaajuus (5 cr)
Course unit code: YTIP2100
General information
- Credits
- 5 cr
- Teaching language
- English
- Responsible person
- Tuomo Sipola
Objective
The student understands the purpose of artificial intelligence and knows the importance and possibilities of data. The student understands the importance of data quality and the ethics of artificial intelligence. The student will know the steps of data analytics/machine learning/deep learning processes. The student has knowledge and skills to plan a data strategy.
Course competences
EUYKN EUR-ACE: Knowledge and Understanding, Master's Degree
EUYCT EUR-ACE: Communication and Team-working, Master's Degree
EUYLL EUR-ACE: Lifelong Learning, Master's Degree
Content
The key topics of the course are:
The possibilities of data
Ethics of Artificial Intelligence (AI)
The importance of data quality
Methodology of Data analytics (DA) and AI
DA and AI project process and management
Data strategy
Open source tools to DA, ML and AI
Assessment criteria, satisfactory (1)
**Assessment criteria, sufficient 1, satisfactory 2
Sufficient 1: Student has sufficient knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a partially comprehensive data strategy and describe the DA/AI process. In addition, student understands the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors at a sufficient level.
Satisfactory 2: Student has satisfactory knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a partially comprehensive data strategy and describe the DA/AI process. In addition, student understands the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors at a satisfactory level.
Assessment criteria, good (3)
Good 3: Student has good knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a partially comprehensive data strategy and describe the DA/AI process. In addition, student understands the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors well.
Very Good 4: Student has very good knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a comprehensive data strategy and describe the DA/AI process. In addition, student understands the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors very well.
Assessment criteria, excellent (5)
Excellent 5: Student has excellent knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a comprehensive data strategy and describe the DA/AI process. In addition, student understands excellently the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors.
Execution methods
face-to-face learning (lectures, discussion) and distance learning (exercises)