Introduction to Data Analytics and Artificial Intelligence (3 cr)
Code: TTC2050-3018
General information
- Enrollment
-
20.11.2023 - 04.01.2024
Registration for the implementation has ended.
- Timing
-
08.01.2024 - 30.04.2024
Implementation has ended.
- Number of ECTS credits allocated
- 3 cr
- Local portion
- 3 cr
- Mode of delivery
- Face-to-face
- Unit
- School of Technology
- Campus
- Lutakko Campus
- Teaching languages
- Finnish
- Seats
- 20 - 35
- Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Realization has 4 reservations. Total duration of reservations is 6 h 0 min.
| Time | Topic | Location |
|---|---|---|
|
Tue 05.03.2024 time 11:30 - 13:00 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3018, Tietoverkkotekniikka TSAT0530-3009 |
P2_D426
Mediatekniikka
|
|
Tue 12.03.2024 time 11:30 - 13:00 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3018, Tietoverkkotekniikka TSAT0530-3009 |
P2_D426
Mediatekniikka
|
|
Tue 19.03.2024 time 11:30 - 13:00 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3018, Tietoverkkotekniikka TSAT0530-3009 |
Verkko/Online (KYHA)
|
|
Tue 26.03.2024 time 11:30 - 13:00 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3018, Tietoverkkotekniikka TSAT0530-3009 |
P2_D426
Mediatekniikka
|
Evaluation scale
0-5
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
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
Location and time
Online lectures and, in addition, guidance in doing exercises in class
Materials
Course material page (lecture materials, exercises)
Teaching methods
Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises
Student workload
Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 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.
Qualifications
Ohjelmoinnin perusteet
Further information
The assessment of the course consists of returned exercises.