Study Guide

Learning outcomes

The student is able to
- design and use appropriate data structures and algorithms
- create a simple GUI for IoT-system
- transfer data securely from IoT device to a cloud using platform services (programming point of view)
- use version control systems in software development
- design and evaluate ML and AI algorithms
- work as an active team member in an ICT project with modern teamwork methods and tools

Timing and attendance

Attending classes is required according to the schedules defined in the Time-edit.

Learning material and recommended literature

Material shared in the Moodle platform, presented during the lessons, www*.

These will be clarified during the class hours.

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying. This includes the defined lectures, self-studying and exercises.

Contents

The course consists of three sub-areas:
- Data structures and Algorithms
- IoT Pipeline
- IoT Project

Additional information for students: previous knowledge etc.

Basic understanding of
- Programming
- Web development
- GIT
- IoT concept

Assessment criteria

Course evaluation consists of the weekly tasks and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criteria.

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

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

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

The student and group deliverables (for example, presentations) are clear and logical.

They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's deliverables reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

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

Student and group deliverables (for example, presentations) are clear and logical.

The student's and group's deliverables also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- Recognize the main components of an embedded system and understand the system architecture
- Describe the properties of different electronics components and choose appropriate components for the application
- Design and implement embedded software in the C programming language
- Design and implement a simple embedded device

Implementation and methods of teaching

Lectures, programming exercises, and practical work.

Timing and attendance

Attending classes is required according to the schedules defined in the Time-edit.

Learning material and recommended literature

Material announced during the lectures

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 9 ECTS, which corresponds to an average of 250 hours of studying. This includes the defined lectures, studying and exercises.

Contents

- Applications of embedded systems in various industries
- Basic knowledge of the components
- Embedded system programming
- Signal handling (digital and analog I/O)
- Designing embedded systems
- Prototype development

Additional information for students: previous knowledge etc.

Programming basics with Python

Assessment criteria

Graded practical work. No exam.

Assessment scale

1-5

Failed (0)

The requirements for the skill level 1 described below are not met.

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

The student is able to design and implement a part of the hardware or software of an embedded device. The device fulfills most of the requirements governing it, and the architecture of the hardware or software is documented. The student is able to present their work to others.

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

The student is able to design and implement a part of the hardware or software of an embedded device. The device fulfills the requirements governing it, and the requirements as well as the architecture of the hardware or software is documented. The software or hardware is designed with modularity taken into account. The student is able to present their work to others and answer questions.

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

The student is able to design and implement a part of the hardware or software of an embedded device. The device fulfills the requirements governing it. The architecture of the software or hardware is documented, and the design decisions made during the architecture design are documented and justified deriving from the requirements, when applicable. The software or hardware is designed with modularity and testability taken into account, and the fulfillment of the requirements is shown with tests. The student is able to present their work to others and answer questions. The student completes the practical work within the given schedule.

Learning outcomes

The student is able to
- create a scalable restful API-services for IoT data
- implement ML and AI operations also in edge devices
- use appropriate databases to store IoT data in the platform
- work as a team leader in an ICT project and a member in a multidisciplinary project

Assessment scale

1-5

Learning outcomes

The student is able to
- understands the role of ICT in engineering
- describe the automation system at a general level
- describe the concepts and principles of industrial ICT
- understand the role of the data in ICT engineering
- use common digital documentation and communication tools in the work of an engineering
- understand project based team work methods and principles in engineering
- create a program using structured programming language
- understand HTML and CSS basics
- understand the basics of statistical thinking

Timing and attendance

Attending classes is required according to the schedules defined in the Time-edit.

Learning material and recommended literature

Material is shared in the Moodle platform and some presented during the lessons.

Alternative completion methods

None

Working life cooperation

None

Learning environment

Lahti M19 Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying. This includes the defined lectures, self-studying and exercises.

Contents

The course consists of four sub-areas:

- Programming Basics
- Digitalisation, ICT and automation
- Web Development
- Digital Tools and Data

Additional information for students: previous knowledge etc.

None

Assessment scale

1-5

Learning outcomes

The student is able to
- create a program using object-oriented programming language with databases (in the cloud too)
- understand the principles of user interfaces
- understand operating systems principles
- understand the role of the cloud platform in an IoT pipeline
- explain the structure of the IoT data pipeline, the meaning of the parts of the pipeline and principles of the machine learning and artificial intelligence
- understand the requirements of sensor data in the data value chain.
- understand the basic principles of the secure data transfer from the IoT device to the IoT data pipeline

Implementation and methods of teaching

Lectures and classes will be held at the Lahti campus

Timing and attendance

Course is held during the second semester.

Lectures will be held according to the timetable.

Attending on the lectures is highly desirable.

Learning material and recommended literature

Material provided during the lectures and in the course's Moodle page.

Learning environment

Study material and instructions in the Moodle platform.

Lectures on the Lahti campus

Student time use and work load

Course (15 ECTs) is divided into 6 sub modules. The course requires approximately 405h of work and includes lectures, self studying and exercises.

Contents

Topics:
- Object-oriented programming
- Databases
- IoT Pipeline and cloud platform
- Introduction to operating systems
- Introduction to ML and AI
- Secure data transfer

Additional information for students: previous knowledge etc.

Programming basics with Python

Assessment criteria

Grade scale: 0-5

Course evaluation consists of the weekly tasks, a project, and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criterias.

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

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

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

Student and group presentations are clear and logical. They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's presentations reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

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

The student's and group's presentations also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- use containers and virtualization as a programming and production platform for software systems
- design, create and manage a virtualized environment for an application project
- compare different hypervisors and cloud services to identify the strengths and weaknesses relevant to the solution
- utilize and maintain different operating systems (Linux/Windows) efficiently in a virtualized environment
- manage (private) cloud platform efficiently and securely and understand private/public cloud notable differences

Timing and attendance

The course will be delivered at the Lappeenranta Campus.

Learning material and recommended literature

Material delivered in Moodle, during classes, www*.

Learning environment

Moodle, class (possibly zoom)

Student time use and work load

The indicative amount of work is 405 hrs. The actual amount of work depends on the student.

The required course assignments must be completed.

Contents

Material delivered in Moodle, during classes, www*.

These will be clarified during the class hours.

Assessment criteria

Course evaluation consists of the weekly tasks and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criteria.

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

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

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

The student and group deliverables (for example, presentations) are clear and logical.

They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's deliverables reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

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

Student and group deliverables (for example, presentations) are clear and logical.

The student's and group's deliverables also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- create a program using object-oriented programming language with databases (in the cloud too)
- understand the principles of user interfaces
- understand operating systems principles
- understand the role of the cloud platform in an IoT pipeline
- explain the structure of the IoT data pipeline, the meaning of the parts of the pipeline and principles of the machine learning and artificial intelligence
- understand the requirements of sensor data in the data value chain.
- understand the basic principles of the secure data transfer from the IoT device to the IoT data pipeline

Implementation and methods of teaching

Lectures and classes will be held at the Lahti campus

Timing and attendance

Course is held during the second semester.

Lectures will be held according to the timetable.

Attending on the lectures is highly desirable.

Learning material and recommended literature

Material provided during the lectures and in the course's Moodle page.

Learning environment

Study material and instructions in the Moodle platform.

Lectures on the Lahti campus

Student time use and work load

Course (15 ECTs) is divided into 6 sub modules. The course requires approximately 405h of work and includes lectures, self studying and exercises.

Contents

Topics:
- Object-oriented programming
- Databases
- IoT Pipeline and cloud platform
- Introduction to operating systems
- Introduction to ML and AI
- Secure data transfer

Additional information for students: previous knowledge etc.

Programming basics with Python

Assessment criteria

Grade scale: 0-5

Course evaluation consists of the weekly tasks, a project, and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criterias.

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

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

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

Student and group presentations are clear and logical. They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's presentations reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

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

The student's and group's presentations also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- create a scalable restful API-services for IoT data
- implement ML and AI operations also in edge devices
- use appropriate databases to store IoT data in the platform
- work as a team leader in an ICT project and a member in a multidisciplinary project

Assessment scale

1-5

Learning outcomes

The student is able to
- use containers and virtualization as a programming and production platform for software systems
- design, create and manage a virtualized environment for an application project
- compare different hypervisors and cloud services to identify the strengths and weaknesses relevant to the solution
- utilize and maintain different operating systems (Linux/Windows) efficiently in a virtualized environment
- manage (private) cloud platform efficiently and securely and understand private/public cloud notable differences

Timing and attendance

The course will be delivered at the Lappeenranta Campus.

Learning material and recommended literature

Material delivered in Moodle, during classes, www*.

Learning environment

Moodle, class (possibly zoom)

Student time use and work load

The indicative amount of work is 405 hrs. The actual amount of work depends on the student.

The required course assignments must be completed.

Contents

Material delivered in Moodle, during classes, www*.

These will be clarified during the class hours.

Assessment criteria

Course evaluation consists of the weekly tasks and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criteria.

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

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

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

The student and group deliverables (for example, presentations) are clear and logical.

They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's deliverables reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

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

Student and group deliverables (for example, presentations) are clear and logical.

The student's and group's deliverables also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- design and use appropriate data structures and algorithms
- create a simple GUI for IoT-system
- transfer data securely from IoT device to a cloud using platform services (programming point of view)
- use version control systems in software development
- design and evaluate ML and AI algorithms
- work as an active team member in an ICT project with modern teamwork methods and tools

Timing and attendance

Attending classes is required according to the schedules defined in the Time-edit.

Learning material and recommended literature

Material shared in the Moodle platform, presented during the lessons, www*.

These will be clarified during the class hours.

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying. This includes the defined lectures, self-studying and exercises.

Contents

The course consists of three sub-areas:
- Data structures and Algorithms
- IoT Pipeline
- IoT Project

Additional information for students: previous knowledge etc.

Basic understanding of
- Programming
- Web development
- GIT
- IoT concept

Assessment criteria

Course evaluation consists of the weekly tasks and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criteria.

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

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

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

The student and group deliverables (for example, presentations) are clear and logical.

They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's deliverables reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

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

Student and group deliverables (for example, presentations) are clear and logical.

The student's and group's deliverables also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- Recognize the main components of an embedded system and understand the system architecture
- Describe the properties of different electronics components and choose appropriate components for the application
- Design and implement embedded software in the C programming language
- Design and implement a simple embedded device

Implementation and methods of teaching

Lectures, programming exercises, and practical work.

Timing and attendance

Attending classes is required according to the schedules defined in the Time-edit.

Learning material and recommended literature

Material announced during the lectures

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 9 ECTS, which corresponds to an average of 250 hours of studying. This includes the defined lectures, studying and exercises.

Contents

- Applications of embedded systems in various industries
- Basic knowledge of the components
- Embedded system programming
- Signal handling (digital and analog I/O)
- Designing embedded systems
- Prototype development

Additional information for students: previous knowledge etc.

Programming basics with Python

Assessment criteria

Graded practical work. No exam.

Assessment scale

1-5

Failed (0)

The requirements for the skill level 1 described below are not met.

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

The student is able to design and implement a part of the hardware or software of an embedded device. The device fulfills most of the requirements governing it, and the architecture of the hardware or software is documented. The student is able to present their work to others.

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

The student is able to design and implement a part of the hardware or software of an embedded device. The device fulfills the requirements governing it, and the requirements as well as the architecture of the hardware or software is documented. The software or hardware is designed with modularity taken into account. The student is able to present their work to others and answer questions.

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

The student is able to design and implement a part of the hardware or software of an embedded device. The device fulfills the requirements governing it. The architecture of the software or hardware is documented, and the design decisions made during the architecture design are documented and justified deriving from the requirements, when applicable. The software or hardware is designed with modularity and testability taken into account, and the fulfillment of the requirements is shown with tests. The student is able to present their work to others and answer questions. The student completes the practical work within the given schedule.

Learning outcomes

The student is able to
- understands the role of ICT in engineering
- describe the automation system at a general level
- describe the concepts and principles of industrial ICT
- understand the role of the data in ICT engineering
- use common digital documentation and communication tools in the work of an engineering
- understand project based team work methods and principles in engineering
- create a program using structured programming language
- understand HTML and CSS basics
- understand the basics of statistical thinking

Timing and attendance

Attending classes is required according to the schedules defined in the Time-edit.

Learning material and recommended literature

Material is shared in the Moodle platform and some presented during the lessons.

Alternative completion methods

None

Working life cooperation

None

Learning environment

Lahti M19 Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying. This includes the defined lectures, self-studying and exercises.

Contents

The course consists of four sub-areas:

- Programming Basics
- Digitalisation, ICT and automation
- Web Development
- Digital Tools and Data

Additional information for students: previous knowledge etc.

None

Assessment scale

1-5