Introduction to Data Analytics and Artificial Intelligence (3 cr)
Code: TTC2050-3025
General information
- Timing
-
09.01.2024 - 11.02.2024
Implementation has ended.
- Number of ECTS credits allocated
- 3 cr
- Local portion
- 0 cr
- Virtual portion
- 3 cr
- Mode of delivery
- Distance learning
- Unit
- School of Technology
- Teaching languages
- English
- Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
- Bachelor's Degree Programme in Information and Communications Technology
Materials
Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)
Evaluation scale
0-5
Further information
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Virtual portion
3
Student workload
Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h
Assessment criteria, satisfactory (1)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Assessment criteria, good (3)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Assessment criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Teaching language
en
Teaching methods
Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)
Location and time
Verkossa
Number of ECTS credits allocated
3
Qualifications
Ohjelmoinnin perusteet
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Objective
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice