Network AutomatizationLaajuus (5 cr)
Code: TTC5010
Credits
5 op
Teaching language
- Finnish
Responsible person
- Jarmo Viinikanoja
Objective
You know network automation and related technologies. You understand how the different characteristics of devices affect automation. You are able to use automation in creating and researching networks. You are able to create a topology image that can be used in automation. You are able to create networks automatically.
Purpose of the course
You know network automation and related technologies.
Competences of the course
EUR-ACE: Engineering practice
EUR-ACE: Knowledge and understanding
Content
Equipment
Automation technologies
Topology automation
Validation of settings
Automatic installation of settings
Recovery from errors
Qualifications
Data Networks
Linux basics
Basics of Programming
Assessment criteria, satisfactory (1)
Sufficient 1: The student is familiar with network automation and related technologies. The student understands how the different properties of devices affect automation.
Satisfactory 2: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect device information
Assessment criteria, good (3)
Good 3: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect data from the devices and use it to automatically create a topology image of the environment
Very good 4: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect data from the devices and use it to automatically create a topology image of the environment. The student is able to modify/create the environment automatically
Assessment criteria, excellent (5)
Excellent 5: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect data from the devices and use it to automatically create a topology image of the environment. The student is able to automatically modify/create the environment, taking into account error situations and validation of settings
Enrollment
01.08.2024 - 22.08.2024
Timing
26.08.2024 - 18.12.2024
Number of ECTS credits allocated
5 op
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
Teachers
- Antti Häkkinen
Groups
-
TTV22S5Tieto- ja viestintätekniikka (AMK)
-
TTV22S2Tieto- ja viestintätekniikka (AMK)
-
TTV22S3Tieto- ja viestintätekniikka (AMK)
-
TTV22S1Tieto- ja viestintätekniikka (AMK)
-
TTV22S4Tieto- ja viestintätekniikka (AMK)
Objectives
You know network automation and related technologies. You understand how the different characteristics of devices affect automation. You are able to use automation in creating and researching networks. You are able to create a topology image that can be used in automation. You are able to create networks automatically.
Purpose of the course
You know network automation and related technologies.
Competences of the course
EUR-ACE: Engineering practice
EUR-ACE: Knowledge and understanding
Content
Equipment
Automation technologies
Topology automation
Validation of settings
Automatic installation of settings
Recovery from errors
Learning materials and recommended literature
Materials in the e-learning environment.
Teaching methods
- lectures
- independent study
- small group learning
- exercises
- learning tasks
Practical training and working life connections
- visiting lecturers
Exam dates and retake possibilities
The possible date and method of the exam will be announced in the course opening.
Alternative completion methods
The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.
Student workload
One credit (1 Cr) corresponds to an average of 27 hours of work.
- lectures 20 h
- exercises 60 h
- assignment 25 h
- independent study 30 h
Total 135 h
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: The student is familiar with network automation and related technologies. The student understands how the different properties of devices affect automation.
Satisfactory 2: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect device information
Evaluation criteria, good (3-4)
Good 3: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect data from the devices and use it to automatically create a topology image of the environment
Very good 4: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect data from the devices and use it to automatically create a topology image of the environment. The student is able to modify/create the environment automatically
Evaluation criteria, excellent (5)
Excellent 5: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect data from the devices and use it to automatically create a topology image of the environment. The student is able to automatically modify/create the environment, taking into account error situations and validation of settings
Prerequisites
Data Networks
Linux basics
Basics of Programming
Enrollment
01.08.2023 - 24.08.2023
Timing
28.08.2023 - 19.12.2023
Number of ECTS credits allocated
5 op
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
Teachers
- Karo Saharinen
- Jarmo Viinikanoja
Groups
-
TTV21S3Tieto- ja viestintätekniikka (AMK)
-
TTV21S5Tieto- ja viestintätekniikka (AMK)
-
TTV21S2Tieto- ja viestintätekniikka (AMK)
-
TTV21S1Tieto- ja viestintätekniikka (AMK)
Objectives
You know network automation and related technologies. You understand how the different characteristics of devices affect automation. You are able to use automation in creating and researching networks. You are able to create a topology image that can be used in automation. You are able to create networks automatically.
Purpose of the course
You know network automation and related technologies.
Competences of the course
EUR-ACE: Engineering practice
EUR-ACE: Knowledge and understanding
Content
Equipment
Automation technologies
Topology automation
Validation of settings
Automatic installation of settings
Recovery from errors
Learning materials and recommended literature
Materials in the e-learning environment.
Teaching methods
- lectures
- independent study
- small group learning
- exercises
- learning tasks
Practical training and working life connections
- visiting lecturers
Exam dates and retake possibilities
The possible date and method of the exam will be announced in the course opening.
Alternative completion methods
The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.
Student workload
One credit (1 Cr) corresponds to an average of 27 hours of work.
- lectures 20 h
- exercises 60 h
- assignment 25 h
- independent study 30 h
Total 135 h
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: The student is familiar with network automation and related technologies. The student understands how the different properties of devices affect automation.
Satisfactory 2: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect device information
Evaluation criteria, good (3-4)
Good 3: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect data from the devices and use it to automatically create a topology image of the environment
Very good 4: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect data from the devices and use it to automatically create a topology image of the environment. The student is able to modify/create the environment automatically
Evaluation criteria, excellent (5)
Excellent 5: The student knows network automation and related technologies. The student understands how the different properties of devices affect automation. The student knows how to automatically collect data from the devices and use it to automatically create a topology image of the environment. The student is able to automatically modify/create the environment, taking into account error situations and validation of settings
Prerequisites
Data Networks
Linux basics
Basics of Programming