Cloud Computing Fundamentals and Machine Learning (5 cr)
Code: TX00EX91-3002
General information
- Enrollment
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02.12.2024 - 16.03.2025
Registration for the implementation has ended.
- Timing
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17.03.2025 - 11.05.2025
Implementation is running.
- Number of ECTS credits allocated
- 5 cr
- Mode of delivery
- On-campus
- Unit
- (2019-2024) School of ICT
- Campus
- Karaportti 2
- Teaching languages
- English
- Seats
- 0 - 35
- Degree programmes
- Degree Programme in Information Technology
- Teachers
- Erik Pätynen
- Sami Ben Cheikh
- Groups
-
tivivaihto_k25Tivi-vaihto, kevät 2025
-
ICT23-SI-NSmart IoT Systems: IoT and Networks
- Course
- TX00EX91
Implementation has 16 reservations. Total duration of reservations is 48 h 0 min.
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Tue 18.03.2025 time 09:00 - 12:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 18.03.2025 time 13:00 - 16:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 25.03.2025 time 09:00 - 12:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 25.03.2025 time 13:00 - 16:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 01.04.2025 time 09:00 - 12:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 01.04.2025 time 13:00 - 16:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 08.04.2025 time 09:00 - 12:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 08.04.2025 time 13:00 - 16:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 15.04.2025 time 09:00 - 12:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 15.04.2025 time 13:00 - 16:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 22.04.2025 time 09:00 - 12:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 22.04.2025 time 13:00 - 16:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 29.04.2025 time 09:00 - 12:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 29.04.2025 time 13:00 - 16:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 06.05.2025 time 09:00 - 12:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
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Tue 06.05.2025 time 13:00 - 16:00 (3 h 0 min) |
Cloud Computing Fundamentals and Machine Learning TX00EX91-3002 |
Online
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Objective
Upon a successful completion of the course, the student
• knows the basics of cloud computing
• can identify global infrastructure components of cloud computing
• knows the basics of implementation and architecture of public cloud computing
• understands the basics of machine learning and knows how machine learning is used to resolve problems.
Content
• Cloud computing concepts
• Overview of cloud infrastructure
• Core cloud services
• Basics of cloud architecture
• Automatic Scaling and Monitoring
• Basics of machine learning
• Machine learning processes
Evaluation scale
0-5
Assessment criteria, satisfactory (1)
The student
• has achieved the objectives of the course
• is able to identify, define and use concepts and models in the subject area of the course
• understands the conditions and principles of the development of expertise.
Assessment criteria, good (3)
The student
• has achieved the objectives of the course well, although there are still areas where knowledge and skills need to be improved
• has a good understanding of the concepts and models of the subject matter of the course and is able to carry out a reasoned analysis
• is able to apply what they have learned in learning and working life situations
• understands the importance of expertise in the ICT field and is able to analyse their own expertise.
Assessment criteria, excellent (5)
The student
• has achieved the objectives of the course with excellent marks
• has an excellent command of the concepts and models of the subject matter of the course
• is able to analyse clearly and reasonably and propose practical development measures
• has a good ability to apply what they have learned in learning and working life situations
• is able to analyse expertise in the ICT field and their own development towards expertise.
Assessment criteria, approved/failed
The student
• has achieved the objectives of the course
• is able to identify, define and use concepts and models in the subject area of the course
• understands the conditions and principles of the development of expertise.