Network Automatization (5 cr)

Evaluation scale

0-5

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

Materials

Materials in the e-learning environment.

Teaching methods

- lectures
- independent study
- small group learning
- exercises
- learning tasks

Employer connections

- visiting lecturers

Exam schedules

The possible date and method of the exam will be announced in the course opening.

Completion alternatives

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

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

Qualifications

Data Networks
Linux basics
Basics of Programming