Introduction to Data Analytics and Artificial Intelligence (3 cr)

Code: TTC2050-3032

General information

Timing: 13.01.2025 - 09.02.2025
Implementation has ended.

Number of ECTS credits allocated: 3 cr

Local portion: 3 cr

Mode of delivery: Contact learning

Unit: School of Technology

Teaching languages: English; Finnish

Degree programmes: Bachelor's Degree Programme in Information and Communications Technology; Bachelor's Degree Programme in Information and Communications Technology

Teachers: Antti Häkkinen

Groups: ZJA25KTIDA1
Avoin amk, Data-analytiikka 1, Verkko; ZJA25KTI
Avoin AMK, tekniikka, ICT

Course: TTC2050

Materials

Course website (lecture material, exercises, recorded lecture videos)

Evaluation scale

0-5

Further information

The evaluation of the course consists of returned exercises.

Student workload

Getting to know the online lecture material 35 hours (recorded lectures with teacher-led exercises)
Distance learning 46 hours (exercises)
A total of 81 hours

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

Teaching methods

Distance learning (exercises, familiarization with lecture material, recorded videos of practical examples)

Location and time

Online

Number of ECTS credits allocated

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