Study Guide

Learning outcomes

The student is able to
- act as a member of the project team as a data network expert
- guide and lead other specialist when it comes to their own area of expertise
- make conclusions based on the success of the client project

Assessment scale

1-5

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
- 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

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 knows how
- explain the importance of graphic communication in communication
- design content through graphic communication
- implement content through graphical communication

Implementation and methods of teaching

Lectures are presented once a week according to the schedule.
Implementation simultaneously face to face and Online
Lectures are recorded

Timing and attendance

The implementation period of the course: 7th of January - 30th of April, 2024

Learning material and recommended literature

Materials from software vendors and networks.
Moodle materials (https://moodle.lut.fi/)

Learning environment

Computer laboratory

Student time use and work load

Lectures + working time 4 hours per week, the total amount of working time 135h

Contents

In the course, you get to know the basics of photoshop and practice producing digital material with the help of various exercises. Teaching takes place with Adobe products.

Assessment criteria

Assessment is based on the returned assignments

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 use and create the basic 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 features of the softwares used in the course in various ways.

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

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

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
- Act as a leading software expert in multidisciplinary game and mobile development projects
- Design and implement a hybrid mobile application
- design and implement responsive Mobile first and SPA applications

Implementation and methods of teaching

Studying takes place in e-learning platform moodle, Zoom and a classroom.
Implementation is hybrid: contact teaching in the classroom and at the same time in the zoom.
The teaching methods used are lectures, as well as applied exercises based on examples.
Some of the time is used in coding the exercises.

Timing and attendance

Presence and personal activity are desirable, monitored, and affect evaluation. The course is approximately 3-4 hours per week and is scheduled for the entire spring 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.

Alternative completion methods

Contant teacher.

Working life cooperation

-

Learning environment

The virtual Moodle e-learning platform is used as the information and organization environment for the course. Online students uses Zoom. 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 time resource for the student is approximately 135h (including lectures and self study)

Contents

The course teaches the development of mobile applications using hybrid programming approach and the technologies needed in them.
Current themes include:
- Hybrid mobile programming concepts, technologies, tools and frameworks
- Cross-platform development is done using React-Native framework

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 Typescript(Javascript) in the mobile environment. Knowledge of the basics of relational databases is also useful.

Prior knowledge:
Basic programming and object-oriented programming skills.
Www-, html and css-basics. Javascript and Typescript programming.

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
- explain IoT development environments and systems
- develop IoT systems
- analyze IoT development environments and systems

Implementation and methods of teaching

Lectures and exercises online

Timing and attendance

Spring 2025, mandatory participation in first lecture

Learning material and recommended literature

Material in Moodle

Exam retakes

Re-take exam

Learning environment

Zoom and Moodle

Student time use and work load

130 hours depending on the student

Contents

Working with Cisco CCNA NetAcad

Assessment criteria

Exams

Assessment scale

1-5

Failed (0)

Under 60% from exams

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

Over 60% from exams

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

Over 75% from exams

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

Over 90% from exams

Learning outcomes

Student can
- act a specialist in a customer project
- lead a team in a customer project
- take into account the profitability of the project

Implementation and methods of teaching

Lectures and exercises online

Timing and attendance

Spring 2025, mandatory participation in first lecture

Learning material and recommended literature

Material in Moodle

Exam retakes

Re-take exam

Learning environment

Zoom and Moodle

Student time use and work load

130 hours depending on the student

Contents

Working with Cisco CCNA NetAcad

Assessment criteria

Exams

Assessment scale

1-5

Failed (0)

Under 60% from exams

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

Over 60% from exams

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

Over 75% from exams

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

Over 90% from exams

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
- explain IoT communication technologies
- describe IoT communication systems
- plan a secure IoT communication system
- have the knowledge and skills of Cisco CCNA (5 - 15 ects)

Implementation and methods of teaching

Lectures and exercises online

Timing and attendance

Spring 2025, mandatory participation in first lecture

Learning material and recommended literature

Material in Moodle

Exam retakes

Re-take exam

Learning environment

Zoom and Moodle

Student time use and work load

130 hours depending on the student

Contents

Working with Cisco CCNA NetAcad

Assessment scale

1-5

Failed (0)

Under 60% from exams

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

Over 60% from exams

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

Over 75% from exams

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

Over 90% from exams

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
- 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 knows how
- explain the basic structure of 3D models
- preferably 3D models for different uses
- Create and edit 3D models with different techniques
- create and edit 3D model materials
- use the basic features of the 3D modeling program
- create digital visualizations

Implementation and methods of teaching

Lectures are presented once a week according to the schedule.
Implementation simultaneously face to face and Online
Lectures are recorded

Timing and attendance

The implementation period of the course: 7th of January - 30th of April, 2024

Learning material and recommended literature

Materials from software vendors and networks.
Moodle materials (https://moodle.lut.fi/)

Alternative completion methods

Competency verification with previous 3D modelling

Learning environment

Computer laboratory

Student time use and work load

Lectures + working time 4 hours per week, the total amount of working time 135h

Contents

In the course, you get to know the basics of 3D modelling and practice 3D modelling with the help of various exercises. Teaching takes place with Blender software.

Assessment criteria

Assessment based on the returned assignments.

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 use and create the basic 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 in many ways.

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 as well. The visual layout of the returned assignments is well implemented.

Learning outcomes

The student is able to
- design a native mobile application
- implement a native mobile application
- compare the differences between hybrid and native mobile applications

Implementation and methods of teaching

Lectures and programming demonstrations in classes-

Timing and attendance

Lectures on Mondays at 8:15-11:00 from 16 January 2023. Lectures in class M19_224 and online using the zoom tool. The link can be found on the course's moodle page. https://moodle.lut.fi.
Attendance is desirable, but the recording links will be on the moodle page.

Learning material and recommended literature

Materials on the course's moodle page.

Learning environment

https://moodle.lut.fi

Contents

We create android applications using the Android Studio tool. Recommended to install in advance.

Additional information for students: previous knowledge etc.

Java programming skills recommended.

Assessment criteria

Mandatory exercises.

Assessment scale

1-5

Failed (0)

The minimum requirements for the practice work are not met.

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

The minimum requirements for practice work are met.

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

All functional requirements of the exercises are met.

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

All the functional requirements of the exercises are met and good programming practice has been followed.

Learning outcomes

The student is able to
- design and use basic software testing methods
- use software maintenance systems
- design the software to be maintained

Assessment scale

1-5

Learning outcomes

The student is able to
- explain different methods of software engineering
- use agile methods in software projects
- act as a software developer in multidisciplinary projects
- describe different software architectures and use them in development

Assessment scale

1-5

Learning outcomes

The student is able
- explains the object paradigm
- use different programming languages ??in the development of an object-based application
- use collection classes and their algorithms in different programming languages ??and apply them in different environments

Implementation and methods of teaching

Lectures in class room / online.Lectures will be recorded.
Programming exercises.

Timing and attendance

11th Jan 2023 - 30th Apr 2023
no mandatory attendance.
lecture recordings available.

Learning material and recommended literature

Material offered on the Moodle page.

Learning environment

Materials in Moodle.
Compiler environments for C++ and Java programming languages.

Contents

C++ basics & STL library. Java basics & JCF library.

Assessment scale

1-5

Failed (0)

The minimum requirements for the training work are not met.

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

The minimum requirements for practice work are met.

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

One of the two compulsory exercises completed in accordance with the requirements.

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

Both compulsory exercises completed in accordance with the requirements.

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
- justify the use of different basic data structures and algorithms in programming
- use basic data structures and algorithms in software design and implementation

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
- 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
- Design content for the web game environment
- Implement a we-play environment
- compare and interpret technologies in the web gaming environment

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
- 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
- justify the use of different basic data structures and algorithms in programming
- use basic data structures and algorithms in software design and implementation

Assessment scale

1-5

Learning outcomes

The student is able to
- Act as a leading software expert in multidisciplinary game and mobile development projects
- Design and implement a hybrid mobile application
- design and implement responsive Mobile first and SPA applications

Implementation and methods of teaching

Studying takes place in e-learning platform moodle, Zoom and a classroom.
Implementation is hybrid: contact teaching in the classroom and at the same time in the zoom.
The teaching methods used are lectures, as well as applied exercises based on examples.
Some of the time is used in coding the exercises.

Timing and attendance

Presence and personal activity are desirable, monitored, and affect evaluation. The course is approximately 3-4 hours per week and is scheduled for the entire spring 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.

Alternative completion methods

Contant teacher.

Working life cooperation

-

Learning environment

The virtual Moodle e-learning platform is used as the information and organization environment for the course. Online students uses Zoom. 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 time resource for the student is approximately 135h (including lectures and self study)

Contents

The course teaches the development of mobile applications using hybrid programming approach and the technologies needed in them.
Current themes include:
- Hybrid mobile programming concepts, technologies, tools and frameworks
- Cross-platform development is done using React-Native framework

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 Typescript(Javascript) in the mobile environment. Knowledge of the basics of relational databases is also useful.

Prior knowledge:
Basic programming and object-oriented programming skills.
Www-, html and css-basics. Javascript and Typescript programming.

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 a native mobile application
- implement a native mobile application
- compare the differences between hybrid and native mobile applications

Implementation and methods of teaching

Lectures and programming demonstrations in classes-

Timing and attendance

Lectures on Mondays at 8:15-11:00 from 16 January 2023. Lectures in class M19_224 and online using the zoom tool. The link can be found on the course's moodle page. https://moodle.lut.fi.
Attendance is desirable, but the recording links will be on the moodle page.

Learning material and recommended literature

Materials on the course's moodle page.

Learning environment

https://moodle.lut.fi

Contents

We create android applications using the Android Studio tool. Recommended to install in advance.

Additional information for students: previous knowledge etc.

Java programming skills recommended.

Assessment criteria

Mandatory exercises.

Assessment scale

1-5

Failed (0)

The minimum requirements for the practice work are not met.

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

The minimum requirements for practice work are met.

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

All functional requirements of the exercises are met.

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

All the functional requirements of the exercises are met and good programming practice has been followed.

Learning outcomes

The student knows how
- Design content for the web game environment
- Implement a we-play environment
- compare and interpret technologies in the web gaming environment

Assessment scale

1-5

Learning outcomes

The student knows how
- explain the importance of graphic communication in communication
- design content through graphic communication
- implement content through graphical communication

Implementation and methods of teaching

Lectures are presented once a week according to the schedule.
Implementation simultaneously face to face and Online
Lectures are recorded

Timing and attendance

The implementation period of the course: 7th of January - 30th of April, 2024

Learning material and recommended literature

Materials from software vendors and networks.
Moodle materials (https://moodle.lut.fi/)

Learning environment

Computer laboratory

Student time use and work load

Lectures + working time 4 hours per week, the total amount of working time 135h

Contents

In the course, you get to know the basics of photoshop and practice producing digital material with the help of various exercises. Teaching takes place with Adobe products.

Assessment criteria

Assessment is based on the returned assignments

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 use and create the basic 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 features of the softwares used in the course in various ways.

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

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

Learning outcomes

The student is able to
- explain IoT development environments and systems
- develop IoT systems
- analyze IoT development environments and systems

Implementation and methods of teaching

Lectures and exercises online

Timing and attendance

Spring 2025, mandatory participation in first lecture

Learning material and recommended literature

Material in Moodle

Exam retakes

Re-take exam

Learning environment

Zoom and Moodle

Student time use and work load

130 hours depending on the student

Contents

Working with Cisco CCNA NetAcad

Assessment criteria

Exams

Assessment scale

1-5

Failed (0)

Under 60% from exams

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

Over 60% from exams

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

Over 75% from exams

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

Over 90% from exams

Learning outcomes

The student is able to
- explain IoT communication technologies
- describe IoT communication systems
- plan a secure IoT communication system
- have the knowledge and skills of Cisco CCNA (5 - 15 ects)

Implementation and methods of teaching

Lectures and exercises online

Timing and attendance

Spring 2025, mandatory participation in first lecture

Learning material and recommended literature

Material in Moodle

Exam retakes

Re-take exam

Learning environment

Zoom and Moodle

Student time use and work load

130 hours depending on the student

Contents

Working with Cisco CCNA NetAcad

Assessment scale

1-5

Failed (0)

Under 60% from exams

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

Over 60% from exams

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

Over 75% from exams

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

Over 90% from exams

Learning outcomes

Student can
- act a specialist in a customer project
- lead a team in a customer project
- take into account the profitability of the project

Implementation and methods of teaching

Lectures and exercises online

Timing and attendance

Spring 2025, mandatory participation in first lecture

Learning material and recommended literature

Material in Moodle

Exam retakes

Re-take exam

Learning environment

Zoom and Moodle

Student time use and work load

130 hours depending on the student

Contents

Working with Cisco CCNA NetAcad

Assessment criteria

Exams

Assessment scale

1-5

Failed (0)

Under 60% from exams

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

Over 60% from exams

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

Over 75% from exams

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

Over 90% from exams

Learning outcomes

The student is able to
- explain different methods of software engineering
- use agile methods in software projects
- act as a software developer in multidisciplinary projects
- describe different software architectures and use them in development

Assessment scale

1-5

Learning outcomes

The student is able
- explains the object paradigm
- use different programming languages ??in the development of an object-based application
- use collection classes and their algorithms in different programming languages ??and apply them in different environments

Implementation and methods of teaching

Lectures in class room / online.Lectures will be recorded.
Programming exercises.

Timing and attendance

11th Jan 2023 - 30th Apr 2023
no mandatory attendance.
lecture recordings available.

Learning material and recommended literature

Material offered on the Moodle page.

Learning environment

Materials in Moodle.
Compiler environments for C++ and Java programming languages.

Contents

C++ basics & STL library. Java basics & JCF library.

Assessment scale

1-5

Failed (0)

The minimum requirements for the training work are not met.

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

The minimum requirements for practice work are met.

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

One of the two compulsory exercises completed in accordance with the requirements.

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

Both compulsory exercises completed in accordance with the requirements.

Learning outcomes

The student is able to
- act as a member of the project team as a data network expert
- guide and lead other specialist when it comes to their own area of expertise
- make conclusions based on the success of the client project

Assessment scale

1-5

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
- explain the basic structure of 3D models
- preferably 3D models for different uses
- Create and edit 3D models with different techniques
- create and edit 3D model materials
- use the basic features of the 3D modeling program
- create digital visualizations

Implementation and methods of teaching

Lectures are presented once a week according to the schedule.
Implementation simultaneously face to face and Online
Lectures are recorded

Timing and attendance

The implementation period of the course: 7th of January - 30th of April, 2024

Learning material and recommended literature

Materials from software vendors and networks.
Moodle materials (https://moodle.lut.fi/)

Alternative completion methods

Competency verification with previous 3D modelling

Learning environment

Computer laboratory

Student time use and work load

Lectures + working time 4 hours per week, the total amount of working time 135h

Contents

In the course, you get to know the basics of 3D modelling and practice 3D modelling with the help of various exercises. Teaching takes place with Blender software.

Assessment criteria

Assessment based on the returned assignments.

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 use and create the basic 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 in many ways.

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 as well. The visual layout of the returned assignments is well implemented.

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