Study Guide

Learning outcomes

The student is able to
- utilize mathematical methods to analyze and to predict phenomena
- utilize a modern statistical tool
- visualize data to identify its properties, analysis interpretation and to facilitate further processing

Assessment scale

1-5

Learning outcomes

The student knows how
- design and implement 2D and 3D games for different game platforms
- take advantage of the physics of game engines
- make use of mathematics and physics to implement game dynamics

Implementation and methods of teaching

Content:
Unity 3D advanced features. The course included lectures, project work, and practical assignments.

Timing and attendance

Lectures once per week from January to April.

Learning material and recommended literature

Unity3d documentation and API descriptions. Study material is distributed in Moodle.

Alternative completion methods

Verification of skills, e.g. with the help of a practical game project

Contents

The course introduces the advanced features of the Unity game engine. Students are required to know the basics of the Unity. The course is implemented as laboratory work, which includes knowledge attacks, practical exercises, independent knowledge acquisition and application. The learning environment is an online computer where games can be developed with the Unity game engine.

Additional information for students: previous knowledge etc.

Basic knowledge about 3D Unity and programming with C#

Assessment criteria

Active participation in teaching, returned exercises

Assessment scale

1-5

Assessment criteria: level 1 (assessment scale 1–5)

Can implement the exercises/game project in accordance with the given minimum requirements

Assessment criteria: level 3 (assessment scale 1–5)

Can implement the exercises/game project according to the given requirements and look for alternative solutions/implementation methods. Makes versatile use of the features of the game engine. The source code is clean and the usability is at a good level.

Assessment criteria: level 5 (assessment scale 1–5)

Can implement the exercises/game project according to the given instructions and exceed the customer's expectations. Searches for and critically analyzes alternative solutions/implementation methods. The source code is fully commented and clean. Usability is at a suitable level. The result is visually impressive

Learning outcomes

Student is able to
- explain principles of distribution and data communications concerning distributed embedded systems
- explain the methods, communication protocols and implementation frameworks used in distributed systems
- design and implement an distributed application

Assessment scale

1-5

Learning outcomes

Student can
- Design and implement embedded IoT device using standard data transfer protocols
- Implement Iot hub as cloud service with simple data analysis and visualization application
- utilize unit testing tools to guarantee software quality
- work as a leading software specialist in IoT development project

Assessment scale

1-5

Learning outcomes

The student is able to
- design and implement basic electronic circuits
- implement a simple IoT solution
- implement a simple embedded system program with an appropriate programming language
- implement simple application using standand system calls
- expond an IoT and embedded system use in different applications

Assessment scale

1-5

Learning outcomes

The student is able to
- document basic circuits in electronics
- design a simple IoT solution
- design a simple embedded system program with an appropriate programming language
- design a simple application using standard system calls
- analyze and categorize IoT and embedded system design

Assessment scale

1-5

Learning outcomes

Student is able to
- design and implement a modern web-application
- implement an asynchronous web-application
- use modern frameworks in implementing the web-application

Implementation and methods of teaching

The teaching methods used are distance learning lectures, as well as applied exercises based on examples.

Timing and attendance

Presence and personal activity are desirable, monitored, and affect evaluation. The course is approximately 2 x 2 hours per week and is scheduled for the second semester of the fall (starting from week 44 until xmas).

Learning material and recommended literature

Study material can be found in Moodle. It consists of course lecture slides and other current material. In addition, the student independently searches for both literature sources and reliable sources available on the Internet.

Alternative completion methods

Agreed on demand.

Working life cooperation

-

Exam retakes

-

Learning environment

The virtual Moodle e-learning platform is used as the information and organization environment for the course. This course requires a personal computer and it is a good idea to have administrator rights during the course. The computer OS can be Windows, Linux, or Mac.

Student time use and work load

Lecture session approximately 33.
Total hours for studying approximately 80.

Contents

During this course student learns web-frameworks used in web-services. Browser framework is Angular (or similar).

Additional information for students: previous knowledge etc.

www-technologies, programming basics, Javascript/Typescript basics.

Assessment criteria

The evaluation is based on the level of completion of the tasks assigned to the course and the student's activity.

Assessment scale

1-5

Failed (0)

The student has not achieved the competence objectives of the course.

Assessment criteria: level 1 (assessment scale 1–5)

The student is able to make use of available data sources and make independent solutions to some extent. The tasks to be returned must be completed at the pass level.

Assessment criteria: level 3 (assessment scale 1–5)

The student is able to use and apply the available data sources independently.
The returned tasks must be performed in such a way that they have been correctly and approved in accordance with the assignment. The student participates in the discussion and reflection during the lectures.

Assessment criteria: level 5 (assessment scale 1–5)

The student is able to make use of, critically evaluate and apply available data sources. The student is required to take an active part in the discussion, is a positive interlocutor and promotes the discussion in an essential direction and justifies his or her opinion. The tasks to be returned must be completed in such a way that they meet the objectives of the given assignment at a commendable level.

Learning outcomes

The student is able to
- take advantage of both supervised and unsupervised machine learning in an appropriate way
- implement the fitting of the machine learning model
- take advantage of the supply of cloud services
- take into account the ethical guidelines of the authorities and the technology industry
- make use of existing machine learning ecosystems and equipment

Assessment scale

1-5

Learning outcomes

The student is able to
- explain the possibilities of different server systems
- estimate the usability of different services
- design and implement various server systems with their services

Assessment scale

1-5

Learning outcomes

The student is able to
- compare browser and server technologies
- implement a database-based server application
- work as a leading software expert in multidisciplinary web development projects

Implementation and methods of teaching

Lectures and programming assignments with the teacher and independently.
Studying node.js- / express-based web applications.

Timing and attendance

Timing: September 5, 2022 - December 16, 2022
Presence during classes is desirable. The purpose is to take hours as a hybridist (class + zoom). Lectures become recordings.

Learning material and recommended literature

Material coming to the Moodle environment

Additional information for students: previous knowledge etc.

Basics of Programming, Basics of Object Oriented Programming, Basics of Web Design, Web Interactivity, Programming Languages

Assessment criteria

Returnable assignments, mainly in groups.

Assessment scale

1-5

Assessment criteria: level 1 (assessment scale 1–5)

Exercises returned with minimum specifications.

Assessment criteria: level 3 (assessment scale 1–5)

Exercises returned according to specifications.

Assessment criteria: level 5 (assessment scale 1–5)

The exercises were carried out with excellent performance and the programming was done professionally.

Learning outcomes

The student is able to
- act as an data network expert in a project
- direct other data network technology experts in his / her area of expertise
- direct other information technology project members in data network related questitions
- implement centralized online services in a customer-oriented and cost-conscious manner

Assessment scale

1-5

Learning outcomes

The student knows how
- utilizes modelling in different environments
- take advantage of the advanced features of game engines
- Use new technologies in gaming and augmented reality applications

Implementation and methods of teaching

The second course of 3D modeling, where we move on to more advanced techniques of Blender. The important aspect on the course is modeling for games and game environments. The course is implemented as weekly hybrid lectures and practical exercises.

Timing and attendance

Autumn 2022

Exam retakes

No exam

Learning environment

Moodle.lut.fi and Zoom

Additional information for students: previous knowledge etc.

Basic 3D modeling course completed or equivalent skills

Assessment scale

1-5

Failed (0)

Active participation in teaching, returnable assignments.

Assessment criteria: level 1 (assessment scale 1–5)

The student is able to use advanced features of the software used in the course.

Assessment criteria: level 3 (assessment scale 1–5)

The student is able to use and utilize the 3D modelling features of the software used in the course.

Assessment criteria: level 5 (assessment scale 1–5)

The student masters the software used in the course professionally and is able to apply the lessons learned in the use of other software. The visual layout of the returned assignments is well implemented.

Learning outcomes

Student is able to
- design and use document databases
- design and implement API interfaces using a programming language
- design and implement a scaleable microservice

Implementation and methods of teaching

The teaching methods are lectures (online), as well as applied exercises based on examples.

Timing and attendance

Presence and personal activity are desirable, monitored, and affect evaluation. The course have approximately 3 hours per week and is scheduled for the entire fall semester.

Learning material and recommended literature

Study material can be found in Moodle. It consists of course lecture slides and other current material. In addition, the student independently searches for both literature sources and reliable sources available on the Internet.

Learning environment

The virtual Moodle e-learning platform is used as the information and organization environment for the course. This course requires a personal computer and it is a good idea to have administrator rights during the course. The computer OS can be Windows, Linux, or Mac.

Student time use and work load

Total lectures round 44h. Average time needed to complete 106h.

Contents

The course teaches the development of cloud-based systems and the technologies needed in them.
Current themes include:
- APIs, design and documentation principles
- Restful API architecture
- API documentation and testing tools
- Serverless architecture and micro services
- FaaS Services
- NoSQL databases

In addition, software development uses container technologies (e.g. Docker).

Additional information for students: previous knowledge etc.

The teaching is primarily intended for students of Information and communication technology.
The student is required to have basic knowledge and skills in programming, as well as knowledge of the basics of web technology. Most programs are made in Javascript in the browser and Node environment. Knowledge of the basics of relational databases is also useful.

Assessment criteria

The evaluation is based on the level of completion of the tasks assigned to the course and the student's activity.

Assessment scale

1-5

Failed (0)

The student has not achieved the competence objectives of the course.

Assessment criteria: level 1 (assessment scale 1–5)

The student is able to make use of available data sources and make independent solutions to some extent.
The tasks to be returned must be completed at the pass level.

Assessment criteria: level 3 (assessment scale 1–5)

The student is able to use and apply the available data sources independently.
The returned tasks must be performed in such a way that they have been correctly and approved in accordance with the assignment. The student participates in the discussion and reflection during the lectures.

Assessment criteria: level 5 (assessment scale 1–5)

The student is able to make use of, critically evaluate and apply available data sources. The student is required to take an active part in the discussion, is a positive interlocutor and promotes the discussion in an essential direction and justifies his or her opinion. The tasks to be returned must be completed in such a way that they meet the objectives of the given assignment at a commendable level.

Learning outcomes

The student is able to
- design an adaptive web interface
- implement a javascript based application on different implementation platforms
- expound the usability of the user interface

Implementation and methods of teaching

Lectures and programming assignments with the teacher and independently. Studying typescript / javascript based web applications.
The student knows
- Design an adaptive web interface
- implement a js-based application on different implementation platforms
- interpret the usability of the user interface

Timing and attendance

Timing: September 5, 2022 - December 16, 2022
Presence during classes is desirable. The purpose is to take hours as a hybridist (class + zoom). Lectures become recordings.

Learning material and recommended literature

Material coming to the Moodle environment

Learning environment

https://moodle.lut.fi

Additional information for students: previous knowledge etc.

Basics of Programming, Basics of Object Oriented Programming, Basics of Web Design, Web Interactivity, Programming Languages

Assessment criteria

Returnable assignments, mainly in groups.

Assessment scale

1-5

Failed (0)

Exercises not returned or abandoned.

Assessment criteria: level 1 (assessment scale 1–5)

Exercises returned with minimum specifications.

Assessment criteria: level 3 (assessment scale 1–5)

Exercises returned according to specifications.

Assessment criteria: level 5 (assessment scale 1–5)

The exercises were carried out with excellent user interface and performance efficiency, and the programming was done professionally

Learning outcomes

The student is able to
- explain the basics of operating systems in terms of software development
- implement an embedded system that utilizes a real-time operating system
- analyze the advantages and disadvantages of embedded programming

Assessment scale

1-5

Learning outcomes

The student is able to
- obtain information independently
- do research work using project work methods
- utilize the knowledge and skills gained in a practical project in the research work
- apply research information in practical projects
- write a written report and a seminar presentation
- critically examine professional texts and presentations
- use statistical and probabilistic mathematical methods

Assessment scale

1-5

Learning outcomes

The student is able to
- define most important competences needed in work life
- act as an expert in different jobs
- define future work skills and challenges in work life
- categorize rules in work life
- interpret work life economy, human resources and leadership
- act actively in international IT-environments

Assessment scale

1-5

Learning outcomes

A student can:
- describe different kind of new technologies
- compare suitability of technologies against own needs
- utilize some of new technologies presented on the course

Assessment scale

1-5

Learning outcomes

The student is able to
- describe and recognize the benefits of virtualization and cloud computing when it comes to improving the efficiency of ICT services
- plan and execute a digital service using virtualization and cloud computing in a chosen platform
- discuss and justify the choice of virtualization environment or cloud computing service as a platform for digital services

Assessment scale

1-5

Learning outcomes

The student knows how to:
- describe the foundations of internal, voluntary, and external entrepreneurship
- evaluate the business idea and its chances of success
- assess the strategic importance of innovation and innovation
- use different brainstorming methods
- analyze different innovation processes

Assessment scale

1-5

Learning outcomes

The student is able to
- design and implement basic electronic circuits
- implement a simple IoT solution
- implement a simple embedded system program with an appropriate programming language
- implement simple application using standand system calls
- expond an IoT and embedded system use in different applications

Assessment scale

1-5

Learning outcomes

The student is able to
- take advantage of both supervised and unsupervised machine learning in an appropriate way
- implement the fitting of the machine learning model
- take advantage of the supply of cloud services
- take into account the ethical guidelines of the authorities and the technology industry
- make use of existing machine learning ecosystems and equipment

Assessment scale

1-5

Learning outcomes

Student is able to
- design and implement a modern web-application
- implement an asynchronous web-application
- use modern frameworks in implementing the web-application

Implementation and methods of teaching

The teaching methods used are distance learning lectures, as well as applied exercises based on examples.

Timing and attendance

Presence and personal activity are desirable, monitored, and affect evaluation. The course is approximately 2 x 2 hours per week and is scheduled for the second semester of the fall (starting from week 44 until xmas).

Learning material and recommended literature

Study material can be found in Moodle. It consists of course lecture slides and other current material. In addition, the student independently searches for both literature sources and reliable sources available on the Internet.

Alternative completion methods

Agreed on demand.

Working life cooperation

-

Exam retakes

-

Learning environment

The virtual Moodle e-learning platform is used as the information and organization environment for the course. This course requires a personal computer and it is a good idea to have administrator rights during the course. The computer OS can be Windows, Linux, or Mac.

Student time use and work load

Lecture session approximately 33.
Total hours for studying approximately 80.

Contents

During this course student learns web-frameworks used in web-services. Browser framework is Angular (or similar).

Additional information for students: previous knowledge etc.

www-technologies, programming basics, Javascript/Typescript basics.

Assessment criteria

The evaluation is based on the level of completion of the tasks assigned to the course and the student's activity.

Assessment scale

1-5

Failed (0)

The student has not achieved the competence objectives of the course.

Assessment criteria: level 1 (assessment scale 1–5)

The student is able to make use of available data sources and make independent solutions to some extent. The tasks to be returned must be completed at the pass level.

Assessment criteria: level 3 (assessment scale 1–5)

The student is able to use and apply the available data sources independently.
The returned tasks must be performed in such a way that they have been correctly and approved in accordance with the assignment. The student participates in the discussion and reflection during the lectures.

Assessment criteria: level 5 (assessment scale 1–5)

The student is able to make use of, critically evaluate and apply available data sources. The student is required to take an active part in the discussion, is a positive interlocutor and promotes the discussion in an essential direction and justifies his or her opinion. The tasks to be returned must be completed in such a way that they meet the objectives of the given assignment at a commendable level.

Learning outcomes

The student is able to
- document basic circuits in electronics
- design a simple IoT solution
- design a simple embedded system program with an appropriate programming language
- design a simple application using standard system calls
- analyze and categorize IoT and embedded system design

Assessment scale

1-5

Learning outcomes

Student can
- Design and implement embedded IoT device using standard data transfer protocols
- Implement Iot hub as cloud service with simple data analysis and visualization application
- utilize unit testing tools to guarantee software quality
- work as a leading software specialist in IoT development project

Assessment scale

1-5

Learning outcomes

Student is able to
- explain principles of distribution and data communications concerning distributed embedded systems
- explain the methods, communication protocols and implementation frameworks used in distributed systems
- design and implement an distributed application

Assessment scale

1-5

Learning outcomes

The student is able to
- design an adaptive web interface
- implement a javascript based application on different implementation platforms
- expound the usability of the user interface

Implementation and methods of teaching

Lectures and programming assignments with the teacher and independently. Studying typescript / javascript based web applications.
The student knows
- Design an adaptive web interface
- implement a js-based application on different implementation platforms
- interpret the usability of the user interface

Timing and attendance

Timing: September 5, 2022 - December 16, 2022
Presence during classes is desirable. The purpose is to take hours as a hybridist (class + zoom). Lectures become recordings.

Learning material and recommended literature

Material coming to the Moodle environment

Learning environment

https://moodle.lut.fi

Additional information for students: previous knowledge etc.

Basics of Programming, Basics of Object Oriented Programming, Basics of Web Design, Web Interactivity, Programming Languages

Assessment criteria

Returnable assignments, mainly in groups.

Assessment scale

1-5

Failed (0)

Exercises not returned or abandoned.

Assessment criteria: level 1 (assessment scale 1–5)

Exercises returned with minimum specifications.

Assessment criteria: level 3 (assessment scale 1–5)

Exercises returned according to specifications.

Assessment criteria: level 5 (assessment scale 1–5)

The exercises were carried out with excellent user interface and performance efficiency, and the programming was done professionally

Learning outcomes

The student is able to
- compare browser and server technologies
- implement a database-based server application
- work as a leading software expert in multidisciplinary web development projects

Implementation and methods of teaching

Lectures and programming assignments with the teacher and independently.
Studying node.js- / express-based web applications.

Timing and attendance

Timing: September 5, 2022 - December 16, 2022
Presence during classes is desirable. The purpose is to take hours as a hybridist (class + zoom). Lectures become recordings.

Learning material and recommended literature

Material coming to the Moodle environment

Additional information for students: previous knowledge etc.

Basics of Programming, Basics of Object Oriented Programming, Basics of Web Design, Web Interactivity, Programming Languages

Assessment criteria

Returnable assignments, mainly in groups.

Assessment scale

1-5

Assessment criteria: level 1 (assessment scale 1–5)

Exercises returned with minimum specifications.

Assessment criteria: level 3 (assessment scale 1–5)

Exercises returned according to specifications.

Assessment criteria: level 5 (assessment scale 1–5)

The exercises were carried out with excellent performance and the programming was done professionally.

Learning outcomes

Student is able to
- design and use document databases
- design and implement API interfaces using a programming language
- design and implement a scaleable microservice

Implementation and methods of teaching

The teaching methods are lectures (online), as well as applied exercises based on examples.

Timing and attendance

Presence and personal activity are desirable, monitored, and affect evaluation. The course have approximately 3 hours per week and is scheduled for the entire fall semester.

Learning material and recommended literature

Study material can be found in Moodle. It consists of course lecture slides and other current material. In addition, the student independently searches for both literature sources and reliable sources available on the Internet.

Learning environment

The virtual Moodle e-learning platform is used as the information and organization environment for the course. This course requires a personal computer and it is a good idea to have administrator rights during the course. The computer OS can be Windows, Linux, or Mac.

Student time use and work load

Total lectures round 44h. Average time needed to complete 106h.

Contents

The course teaches the development of cloud-based systems and the technologies needed in them.
Current themes include:
- APIs, design and documentation principles
- Restful API architecture
- API documentation and testing tools
- Serverless architecture and micro services
- FaaS Services
- NoSQL databases

In addition, software development uses container technologies (e.g. Docker).

Additional information for students: previous knowledge etc.

The teaching is primarily intended for students of Information and communication technology.
The student is required to have basic knowledge and skills in programming, as well as knowledge of the basics of web technology. Most programs are made in Javascript in the browser and Node environment. Knowledge of the basics of relational databases is also useful.

Assessment criteria

The evaluation is based on the level of completion of the tasks assigned to the course and the student's activity.

Assessment scale

1-5

Failed (0)

The student has not achieved the competence objectives of the course.

Assessment criteria: level 1 (assessment scale 1–5)

The student is able to make use of available data sources and make independent solutions to some extent.
The tasks to be returned must be completed at the pass level.

Assessment criteria: level 3 (assessment scale 1–5)

The student is able to use and apply the available data sources independently.
The returned tasks must be performed in such a way that they have been correctly and approved in accordance with the assignment. The student participates in the discussion and reflection during the lectures.

Assessment criteria: level 5 (assessment scale 1–5)

The student is able to make use of, critically evaluate and apply available data sources. The student is required to take an active part in the discussion, is a positive interlocutor and promotes the discussion in an essential direction and justifies his or her opinion. The tasks to be returned must be completed in such a way that they meet the objectives of the given assignment at a commendable level.

Learning outcomes

The student knows how
- utilizes modelling in different environments
- take advantage of the advanced features of game engines
- Use new technologies in gaming and augmented reality applications

Implementation and methods of teaching

The second course of 3D modeling, where we move on to more advanced techniques of Blender. The important aspect on the course is modeling for games and game environments. The course is implemented as weekly hybrid lectures and practical exercises.

Timing and attendance

Autumn 2022

Exam retakes

No exam

Learning environment

Moodle.lut.fi and Zoom

Additional information for students: previous knowledge etc.

Basic 3D modeling course completed or equivalent skills

Assessment scale

1-5

Failed (0)

Active participation in teaching, returnable assignments.

Assessment criteria: level 1 (assessment scale 1–5)

The student is able to use advanced features of the software used in the course.

Assessment criteria: level 3 (assessment scale 1–5)

The student is able to use and utilize the 3D modelling features of the software used in the course.

Assessment criteria: level 5 (assessment scale 1–5)

The student masters the software used in the course professionally and is able to apply the lessons learned in the use of other software. The visual layout of the returned assignments is well implemented.

Learning outcomes

A student can:
- describe different kind of new technologies
- compare suitability of technologies against own needs
- utilize some of new technologies presented on the course

Assessment scale

1-5

Learning outcomes

The student is able to
- describe and recognize the benefits of virtualization and cloud computing when it comes to improving the efficiency of ICT services
- plan and execute a digital service using virtualization and cloud computing in a chosen platform
- discuss and justify the choice of virtualization environment or cloud computing service as a platform for digital services

Assessment scale

1-5

Learning outcomes

The student is able to
- explain the possibilities of different server systems
- estimate the usability of different services
- design and implement various server systems with their services

Assessment scale

1-5

Learning outcomes

The student is able to
- act as an data network expert in a project
- direct other data network technology experts in his / her area of expertise
- direct other information technology project members in data network related questitions
- implement centralized online services in a customer-oriented and cost-conscious manner

Assessment scale

1-5

Learning outcomes

The student is able to
- obtain information independently
- do research work using project work methods
- utilize the knowledge and skills gained in a practical project in the research work
- apply research information in practical projects
- write a written report and a seminar presentation
- critically examine professional texts and presentations
- use statistical and probabilistic mathematical methods

Assessment scale

1-5

Learning outcomes

The student knows how to:
- describe the foundations of internal, voluntary, and external entrepreneurship
- evaluate the business idea and its chances of success
- assess the strategic importance of innovation and innovation
- use different brainstorming methods
- analyze different innovation processes

Assessment scale

1-5

Learning outcomes

The student is able to
- define most important competences needed in work life
- act as an expert in different jobs
- define future work skills and challenges in work life
- categorize rules in work life
- interpret work life economy, human resources and leadership
- act actively in international IT-environments

Assessment scale

1-5

Learning outcomes

The student knows how
- design and implement 2D and 3D games for different game platforms
- take advantage of the physics of game engines
- make use of mathematics and physics to implement game dynamics

Implementation and methods of teaching

Content:
Unity 3D advanced features. The course included lectures, project work, and practical assignments.

Timing and attendance

Lectures once per week from January to April.

Learning material and recommended literature

Unity3d documentation and API descriptions. Study material is distributed in Moodle.

Alternative completion methods

Verification of skills, e.g. with the help of a practical game project

Contents

The course introduces the advanced features of the Unity game engine. Students are required to know the basics of the Unity. The course is implemented as laboratory work, which includes knowledge attacks, practical exercises, independent knowledge acquisition and application. The learning environment is an online computer where games can be developed with the Unity game engine.

Additional information for students: previous knowledge etc.

Basic knowledge about 3D Unity and programming with C#

Assessment criteria

Active participation in teaching, returned exercises

Assessment scale

1-5

Assessment criteria: level 1 (assessment scale 1–5)

Can implement the exercises/game project in accordance with the given minimum requirements

Assessment criteria: level 3 (assessment scale 1–5)

Can implement the exercises/game project according to the given requirements and look for alternative solutions/implementation methods. Makes versatile use of the features of the game engine. The source code is clean and the usability is at a good level.

Assessment criteria: level 5 (assessment scale 1–5)

Can implement the exercises/game project according to the given instructions and exceed the customer's expectations. Searches for and critically analyzes alternative solutions/implementation methods. The source code is fully commented and clean. Usability is at a suitable level. The result is visually impressive

Learning outcomes

The student is able to
- utilize mathematical methods to analyze and to predict phenomena
- utilize a modern statistical tool
- visualize data to identify its properties, analysis interpretation and to facilitate further processing

Assessment scale

1-5

Learning outcomes

The student is able to
- explain the basics of operating systems in terms of software development
- implement an embedded system that utilizes a real-time operating system
- analyze the advantages and disadvantages of embedded programming

Assessment scale

1-5