Introduction to Data Analytics and Artificial Intelligence (3 cr)
Code: TTC2050-3031
General information
- Enrollment
-
18.11.2024 - 09.01.2025
Registration for the implementation has ended.
- Timing
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13.01.2025 - 31.03.2025
Implementation has ended.
- Number of ECTS credits allocated
- 3 cr
- Local portion
- 0 cr
- Virtual portion
- 3 cr
- Mode of delivery
- Online learning
- 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 6 reservations. Total duration of reservations is 9 h 0 min.
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Tue 14.01.2025 time 17:00 - 18:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3031 |
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Tue 04.02.2025 time 17:00 - 18:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3031 |
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Tue 18.02.2025 time 17:00 - 18:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3031 |
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Tue 11.03.2025 time 17:00 - 18:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3031 |
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Tue 25.03.2025 time 17:00 - 18:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3031 |
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Tue 01.04.2025 time 17:00 - 18:30 (1 h 30 min) |
Johdatus data-analytiikkaan ja tekoälyyn TTC2050-3031 |
Teams
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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 sessions
Materials
Course material page (lecture materials, exercises)
Teaching methods
- Several online sessions during the implementation (the student can join the online session and get support from the teacher in doing the exercises)
- Distance learning (students can complete the course at their own pace, doing exercises independently)
Student workload
Distance learning 71h (exercises)
Online guidance sessions 10h
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.