Introduction to Data Analytics and Artificial Intelligence (3 cr)
Code: TTC2050-3007
General information
Enrollment
01.11.2022 - 05.01.2023
Timing
09.01.2023 - 28.04.2023
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- English
Seats
0 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TIC21S1Bachelor's Degree Programme in Information and Communications Technology
Objectives
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
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
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Student workload
Lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
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.
Evaluation criteria, good (3-4)
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.
Evaluation 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.
Prerequisites
Ohjelmoinnin perusteet