Introduction to Data Analytics and Artificial Intelligence (3 cr)
Code: TTC2050-3027
General information
- Enrollment
-
18.11.2024 - 09.01.2025
Registration for the implementation has ended.
- Timing
-
13.01.2025 - 31.03.2025
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
- 0 - 35
- Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Realization has 10 reservations. Total duration of reservations is 15 h 0 min.
| Time | Topic | Location |
|---|---|---|
|
Wed 15.01.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
P2_D330
Ohjelmointiluokka
|
|
Wed 22.01.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
P2_D330
Ohjelmointiluokka
|
|
Wed 29.01.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
P2_D330
Ohjelmointiluokka
|
|
Wed 05.02.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
Verkko/Online (KYHA)
|
|
Wed 12.02.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
P2_D330
Ohjelmointiluokka
|
|
Wed 19.02.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
P2_D330
Ohjelmointiluokka
|
|
Wed 05.03.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
P2_D330
Ohjelmointiluokka
|
|
Wed 12.03.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
P2_D330
Ohjelmointiluokka
|
|
Wed 19.03.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
P2_D330
Ohjelmointiluokka
|
|
Wed 26.03.2025 time 08:00 - 09:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3027 |
P2_D330
Ohjelmointiluokka
|
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
Weekly guidance for doing exercises in classrooom
Materials
Course material page (lecture materials, exercises)
Teaching methods
- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)
Student workload
Distance learning 61h (exercises)
Guidance sessions in class 20h
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.
Qualifications
Ohjelmoinnin perusteet
Further information
The assessment of the course consists of returned exercises.