Study Guide

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Location and time

Teaching takes place between weeks 2 and 17. There are 4 hours of lessons per week.

Materials

All study material is offered in the course workspace.

Teaching methods

Teaching is carried out as face-to-face teaching. Studying takes place in a laboratory, where students do laboratory work under supervision and independently produce reports to be evaluated for practice tasks.

Exam schedules

There is no exam in the course, but the course is completed with practice assignments. When renewing a study course, raising a grade, and raising a failed grade as accepted, the valid diploma rules of the Lapland University of Applied Sciences are followed.

Completion alternatives

Other methods of completion of the study course are agreed separately with the teacher responsible for the study course.

Content scheduling

The course takes place between the 3rd and 16th of the calendar weeks. The last day to return the exercises for the course is 30 April 2025.

Evaluation scale

H-5

Assessment methods and criteria

The evaluation is based on the returned exercises, which are scored. A maximum of approx. 33% of the total score is required for a grade of 1 in the course. A maximum of 85% of the total score is required for a grade of 5.

Assessment criteria, fail (0)

The student does not reach the minimum requirements set for the course.

Assessment criteria, satisfactory (1-2)

The student is able to select and implement a sensor or actuator as part of an IoT or automation system.

Assessment criteria, good (3-4)

The student masters the operating principles of sensors and actuators and is able to independently implement the connection of sensors and actuators to an IoT or automation system.

Assessment criteria, excellent (5)

The Student able to plan and implement the electrotechnical installation of measurement sensing and actuators and galvanic separation in a disturbed environment.

Objective

The objective of a Climatic and Reliability Testing course is to provide you an understanding of the principles, methods and techniques for testing the performance of products and systems under various environmental conditions and to assess their reliability under normal and extreme conditions. This course aims to equip you with the knowledge and skills needed to perform climatic and reliability testing, understand the results, and use that information to make informed decisions about product design and development. The goal is to provide you with an understanding of how to perform tests that mimic real-world conditions and to use that information to improve the reliability and performance of products in the field.

Content

Introduction to Climatic and Reliability Testing: Definition, importance, and applications of climatic and reliability testing.

Environmental Testing: Overview of environmental testing, including temperature, humidity, vibration, shock, and altitude testing.

Reliability Testing: Overview of reliability testing, including statistical methods, life testing, accelerated life testing, and stress testing.

Test Equipment and Methods: Overview of test equipment and methods, including test chambers, temperature and humidity controls, and data acquisition systems.

Test Planning and Design: Overview of test planning and design, including selection of test conditions, sample size, and test duration.

Data Analysis and Reporting: Overview of data analysis and reporting, including statistical methods, data presentation, and interpretation of results.

Environmental and Reliability Standards: Overview of environmental and reliability standards, including industry and international standards.

Case Studies: Overview of case studies of successful climatic and reliability testing, including lessons learned and best practices.

Future Trends and Challenges: Overview of future trends and challenges in climatic and reliability testing, including new technologies and emerging trends.

The course may include hands-on laboratory exercises and projects to give students practical experience in performing climatic and reliability tests

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

Knows reasons to do climatic and reliability testing.
- Standards to consider
- General features of the typical climatic tests
- Simulation vs. field testing

Can demonstrate and understand the concepts of reliability engineering.

Assessment criteria, good (3)

Is confident with:
- Reasons to do climatic and reliability testing
- Determine a life test, estimate reliability values from the test data, and set confidence limits on the results.

Assessment criteria, excellent (5)

Is able to:
- Understand Climatic and Reliability Engineering in Business
- Manage Data to Business Case Justification
- Understands the Criticality and Risk
- Understands Life Cycle Considerations
- Can do Root Cause Analysis
- Manage a climatic and reliability testing project

Objective

The student is able to utilize the possibilities of cloud computing services in application development. The student has an overview of different cloud computing services and their features. The student is able to choose a suitable cloud computing service, which may be related to data management, image recognition, text conversion, video processing or other cloud computing.

Content

The course covers various aspects of Cloud Computing and usage examples:
- Deployment of a service provider's Cloud Computing solution
- Identify an object from an image using a cloud computing service
- Processing the text and identifying things from the text
- Programming in the cloud computing service
- Data management using a cloud computing service
- Comparison of cloud computing solutions
- Using a solution that utilizes cloud computing on a mobile device

Materials

Materials will be compiled and made available in the Moodle workspace. If necessary, additional resources and materials will be acquired and added from the internet. This includes documentation and guides for the cloud services used in the course.

Self-study prerequisites, if not familiar: Basics of Python: Familiarity with the basic concepts and syntax of the Python programming language. Basics of Data Management: Understanding of fundamental aspects of data handling, including JSON and databases. Basics of Information Technology: Knowledge of key IT concepts, including understanding what a CPU and GPU are.

Teaching methods

In-person teaching and support for exercises during classes, as well as online materials to support the completion of tasks.

Content scheduling

Theory: Introduction to IaaS, PaaS, and other cloud service options.
Basics and introduction to cloud computing.
Cloud computing: Machine learning in the cloud (Google's Teachable Machine: An interactive tool for machine learning, Google Colab, and possibly other tools), focusing on image recognition and natural language processing.
Basics of cloud platforms and cloud deployment.
Introduction to Firebase/Supabase or other similar technologies.
Ethical and sustainable approaches, covering GDPR, energy consumption, and cost savings.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student understands the principles of cloud computing and cloud service and is able to use cloud computing in simple implementations. The student is able to solve basic problems and search for more information from the digital materials of cloud computing service providers.

Assessment criteria, good (3)

The student understands the principles of cloud computing and cloud service and is able to plan and implement implementations that utilize cloud computing.

The student is able to utilize the features of the cloud computing service. The student is able to choose the most effective solution for a defined need from the services of several cloud computing service providers. The student is able to implement a solution that works with the selected service.

The student is able to solve problems and is able to search for more information from the digital materials of cloud computing service providers.

Assessment criteria, excellent (5)

The student is able to use the cloud computing service smoothly as part of an information system. The student is able to choose the most suitable cloud computing solution for the task. The student is able to apply the features of the cloud computing service in many ways. The student is able to utilize the features of the cloud computing service in software development.

Assessment methods and criteria

Grades are based on the quality, quantity, and comprehensiveness of the exercises.

Objective

The student is able to utilize the possibilities of cloud computing services in application development. The student has an overview of different cloud computing services and their features. The student is able to choose a suitable cloud computing service, which may be related to data management, image recognition, text conversion, video processing or other cloud computing.

Content

The course covers various aspects of Cloud Computing and usage examples:
- Deployment of a service provider's Cloud Computing solution
- Identify an object from an image using a cloud computing service
- Processing the text and identifying things from the text
- Programming in the cloud computing service
- Data management using a cloud computing service
- Comparison of cloud computing solutions
- Using a solution that utilizes cloud computing on a mobile device

Materials

Materials will be compiled and made available in the Moodle workspace. If necessary, additional resources and materials will be acquired and added from the internet. This includes documentation and guides for the cloud services used in the course.

Self-study prerequisites, if not familiar: Basics of Python: Familiarity with the basic concepts and syntax of the Python programming language. Basics of Data Management: Understanding of fundamental aspects of data handling, including JSON and databases. Basics of Information Technology: Knowledge of key IT concepts, including understanding what a CPU and GPU are.

Teaching methods

Online material. Practical exercise support offered in workshops

Content scheduling

Theory: Introduction to IaaS, PaaS, and other cloud service options.
Basics and introduction to cloud computing.
Cloud computing: Machine learning in the cloud (Google's Teachable Machine: An interactive tool for machine learning, Google Colab, and possibly other tools), focusing on image recognition and natural language processing.
Basics of cloud platforms and cloud deployment.
Introduction to Firebase/Supabase or other similar technologies.
Ethical and sustainable approaches, covering GDPR, energy consumption, and cost savings.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student understands the principles of cloud computing and cloud service and is able to use cloud computing in simple implementations. The student is able to solve basic problems and search for more information from the digital materials of cloud computing service providers.

Assessment criteria, good (3)

The student understands the principles of cloud computing and cloud service and is able to plan and implement implementations that utilize cloud computing.

The student is able to utilize the features of the cloud computing service. The student is able to choose the most effective solution for a defined need from the services of several cloud computing service providers. The student is able to implement a solution that works with the selected service.

The student is able to solve problems and is able to search for more information from the digital materials of cloud computing service providers.

Assessment criteria, excellent (5)

The student is able to use the cloud computing service smoothly as part of an information system. The student is able to choose the most suitable cloud computing solution for the task. The student is able to apply the features of the cloud computing service in many ways. The student is able to utilize the features of the cloud computing service in software development.

Assessment methods and criteria

Grades are based on the quality, quantity, and comprehensiveness of the exercises.

Objective

The student is able to design and implement platform-independent mobile applications, taking into account the differences between different mobile platforms.

Content

- Native Mobile Programming vs. Platform-Independent Mobile Programming
- Different implementations of a platform-independent mobile application
- Development of a platform-independent mobile application with the selected technology
- Platform-independent mobile application development process: finalization, testing and deployment

Location and time

Classroom according to the schedule

Materials

All the necessary study materials for the course will be available on Moodle. In addition to the provided materials, up-to-date resources from the internet will also be utilized.

Teaching methods

In the study module, up-to-date methods and materials are utilized in the teaching of cross-platform mobile programming. During the study module, students will familiarize themselves with different cross-platform mobile programming techniques and methods. At the beginning of the study module, the student chooses the method of completion: the options are a project-based approach, focusing on a specific cross-platform technology to deepen skills with the chosen technique, or alternatively, completing smaller exercises throughout the study module that cover multiple different cross-platform mobile programming techniques.

Completion alternatives

To be negotiated separately with the course instructor. Possibility for recognition of prior learning.

Content scheduling

Basics of cross-platform mobile development
Introduction to cross-platform mobile development with chosen technology
Programming language of chosen technology
Setting up the environment
First cross-platform mobile application
Best practices with chosen technology
Problem with cross-platform development - platform specific code
Testing of cross-platform mobile application
Deployment to production

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is familiar with various options for implementing a platform-independent mobile application and is able to implement simple mobile applications with the chosen technology under supervision.

Assessment criteria, good (3)

The student is able to independently design and implement functional platform-independent mobile applications and is able to independently search for and apply external information sources in development work.

Assessment criteria, excellent (5)

The student is able to independently design and implement challenging platform-independent mobile applications and to make effective use of testing and optimization tools in the finalization of a mobile application.

Assessment methods and criteria

The study module is assessed based on exercises, using a scale of 0-5

Objective

The student is able to design and implement platform-independent mobile applications, taking into account the differences between different mobile platforms.

Content

- Native Mobile Programming vs. Platform-Independent Mobile Programming
- Different implementations of a platform-independent mobile application
- Development of a platform-independent mobile application with the selected technology
- Platform-independent mobile application development process: finalization, testing and deployment

Location and time

Zoom classroom according to the schedule

Materials

All the necessary study materials for the course will be available on Moodle. In addition to the provided materials, up-to-date resources from the internet will also be utilized.

Teaching methods

In the study module, up-to-date methods and materials are utilized in the teaching of cross-platform mobile programming. During the study module, students will familiarize themselves with different cross-platform mobile programming techniques and methods. At the beginning of the study module, the student chooses the method of completion: the options are a project-based approach, focusing on a specific cross-platform technology to deepen skills with the chosen technique, or alternatively, completing smaller exercises throughout the study module that cover multiple different cross-platform mobile programming techniques.

Completion alternatives

To be discussed separately with the course instructor. Possibility for recognition of prior learning.

Content scheduling

Basics of cross-platform mobile development
Introduction to cross-platform mobile development with chosen technology
Programming language of chosen technology
Setting up the environment
First cross-platform mobile application
Best practices with chosen technology
Problem with cross-platform development - platform specific code
Testing of cross-platform mobile application
Deployment to production

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is familiar with various options for implementing a platform-independent mobile application and is able to implement simple mobile applications with the chosen technology under supervision.

Assessment criteria, good (3)

The student is able to independently design and implement functional platform-independent mobile applications and is able to independently search for and apply external information sources in development work.

Assessment criteria, excellent (5)

The student is able to independently design and implement challenging platform-independent mobile applications and to make effective use of testing and optimization tools in the finalization of a mobile application.

Assessment methods and criteria

The study module is assessed based on exercises, using a scale of 0-5

Evaluation scale

H-5

Teaching methods

-

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

Approved/Rejected

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Location and time

Teaching takes place between the 3rd and 176h of the study weeks. The course ends at the end of the semester on July 31, 2024. The last return date for the course exercises is, April 30, 2025

Materials

The study course material is offered in the study course workspace.

Teaching methods

Teaching is mainly face-to-face teaching. The course is completed with exercises done in the laboratory. Students produce reports from the exercises independently, which are returned to the workspace used for the course.

Exam schedules

There is no exam in the course. The current guidelines of Lapland AMK apply to renewing the study course and raising the grade.

Completion alternatives

The course can be completed in an alternative way by agreeing with the teacher responsible for teaching the course. The current guidelines of Lapland AMK apply to the identification of previously acquired skills (AHOT).

Content scheduling

The course is completed between the 3rd and 177h of the study weeks.

Evaluation scale

H-5

Assessment methods and criteria

The course is evaluated on a scale of 0 (Fail) to 5 (Commendable). The practice tasks of the course are scored and the passing limit is a maximum of 33% of the maximum score. The limit of a commendable grade is approx. 90% of the maximum score.

Assessment criteria, fail (0)

The student does not reach the minimum requirements set for the course.

Assessment criteria, satisfactory (1-2)

The student understands the basics of wireless data transmission and applies the principles in practice.

Assessment criteria, good (3-4)

The student knows how to choose a suitable standard and technology for wireless data transmission. The student is able to implement a wireless data transfer application in a controlled manner.

Assessment criteria, excellent (5)

The student can plan and implement wireless network solutions independently, taking information security requirements into account.

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Objective

The student knows the basics of the organization's information security work and the standards used. The student acquires the skills for information security development work in his own organization. The student knows the ethical aspects related to information security and data protection. The student is able to adapt to the rapid changes in the information security industry and maintain his skills.

Content

Introduction to information security, assessment of information security risks
Developing information security in companies, incl. required documents
The organization's information security by sub-areas
Data protection, EU data protection regulation and other legislation

Materials

Materials will be presented in Moodle Workspace

Teaching methods

Lessons and seminars

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is able to identify key security threats. The student is able to act in such a way that he / she does not pose a security threat to his / her organization.

Assessment criteria, good (3)

Opiskelija osaa ottaa huomioon lainsäädännön asettamat vaatimukset organisaation tietoturvalliselle toiminnalle. Opiskelija osaa laatia organisaatiolleen ohjeistuksen hyvistä tietoturvakäytännöistä.

Assessment criteria, excellent (5)

The student knows how to act proactively and take into account matters affecting the organization's information security in the national and international operating area, and instructs the operation of her own organization so that information security is part of the way the organization operates.

Assessment methods and criteria

Grading will be based on active partisipating in lectures and excersies.
Submitting papers and delivering persentations.

Assessment criteria, fail (0)

No partisipating and no completed tasks or excersises

Assessment criteria, satisfactory (1-2)

The student gains a good view of Cyber security in the field of Machine learning and has good abilities to further his/ her expertise. The majority of tasks given are completed

Assessment criteria, good (3-4)

The student gains a great view of Cyber security in the field of Machine learning and has great abilities to further his/ her expertise. The majority of tasks given are completed.

Assessment criteria, excellent (5)

The student gains a excellent view of Cyber security n the field of Machine learning and has excellent abilities to further his/ her expertise. All tasks given are completed.

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Assessment criteria, fail (0)

Less than 50% ( 50points ) of the subjects covered in the course are unproven assignments, or alternatively in the learning diary video.

Assessment criteria, satisfactory (1-2)

50-65 points
The student understands the principles of robotics and knows how to use and design simple robotics implementations.
The student is able to implement simple robotics solutions independently.
The student is able to solve basic robotics problems and search for additional information in a guided manner, for example from the digital materials of the Robot Operating System.

Assessment criteria, good (3-4)

65-90 points
The student understands the principles of robotics and knows how to use and plan robotics implementations using a suitable method.
The student is able to implement robotics implementations and solutions independently. The student knows how to use the features offered by robotics actuators and plan a robot implementation. The student knows how to choose the most functional solution for the defined need from among several robotics solutions. The student knows how to implement a working implementation with the selected solution.
The student is able to solve problems and knows how to search for additional information on robotics digital materials.

Assessment criteria, excellent (5)

> 90 points
The student can make robotics applications fluently. The student knows how to choose the solution that best suits the task. The student knows how to apply the opportunities offered by robotics in practice in a versatile way. The student knows how to combine several different practices into a functional whole.

Evaluation scale

H-5

Assessment criteria, fail (0)

Less than 50% ( 50points ) of the subjects covered in the course are unproven assignments, or alternatively in the learning diary video.

Assessment criteria, satisfactory (1-2)

50-65 points
The student understands the principles of robotics and knows how to use and design simple robotics implementations.
The student is able to implement simple robotics solutions independently.
The student is able to solve basic robotics problems and search for additional information in a guided manner, for example from the digital materials of the Robot Operating System.

Assessment criteria, good (3-4)

65-90 points
The student understands the principles of robotics and knows how to use and plan robotics implementations using a suitable method.
The student is able to implement robotics implementations and solutions independently. The student knows how to use the features offered by robotics actuators and plan a robot implementation. The student knows how to choose the most functional solution for the defined need from among several robotics solutions. The student knows how to implement a working implementation with the selected solution.
The student is able to solve problems and knows how to search for additional information on robotics digital materials.

Assessment criteria, excellent (5)

> 90 points
The student can make robotics applications fluently. The student knows how to choose the solution that best suits the task. The student knows how to apply the opportunities offered by robotics in practice in a versatile way. The student knows how to combine several different practices into a functional whole.

Evaluation scale

H-5

Objective

The student knows the components of circuits and is able to analyze and calculate the currents and voltages of simple DC and AC circuits. He understands the meaning and purpose of different components in circuits. The student is able to form appropriate circuits for electronic connections and to simulate connections with a computer-based circuit simulator program.

Content

- Electromagnetic induction
- Power
- Voltage
- Circuits
- Circuit components (voltage sources, resistors, capacitors and inductors)
- RLC circuits, simple filters
- Alternating current
- Circuit simulation and simulation tools

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is familiar with the basics of circuits and related laws such as Ohm's law and Kirchfoff's laws. The student understands the purpose of circuit components and is able to solve simple circuits with a simulation tool.

Assessment criteria, good (3)

The student is familiar with the basics of circuits and related laws such as Ohm's law and Kirchfoff's laws.
The student understands the purpose of circuit components and is able to solve complex circuits with a simulation tool and simple circuits with mathematical methods based on Ohm's and Kirchoff's laws.
The student knows the structures of basic filters and is able to simulate their operation with a simulation tool,

Assessment criteria, excellent (5)

The student will understand and apply the basics of circuits and related laws such as Ohm’s Law and Kirchfoff’s Laws. The student understands the purpose of circuit components and is able to solve complex circuits with a simulation tool and mathematical methods based on Ohm's and Kirchoff's laws.
The student knows and understands the structures and operation of basic filters and is able to design and simulate filters that meet the set requirements with a simulation tool.

Objective

The student knows the components of circuits and is able to analyze and calculate the currents and voltages of simple DC and AC circuits. He understands the meaning and purpose of different components in circuits. The student is able to form appropriate circuits for electronic connections and to simulate connections with a computer-based circuit simulator program.

Content

- Electromagnetic induction
- Power
- Voltage
- Circuits
- Circuit components (voltage sources, resistors, capacitors and inductors)
- RLC circuits, simple filters
- Alternating current
- Circuit simulation and simulation tools

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is familiar with the basics of circuits and related laws such as Ohm's law and Kirchfoff's laws. The student understands the purpose of circuit components and is able to solve simple circuits with a simulation tool.

Assessment criteria, good (3)

The student is familiar with the basics of circuits and related laws such as Ohm's law and Kirchfoff's laws.
The student understands the purpose of circuit components and is able to solve complex circuits with a simulation tool and simple circuits with mathematical methods based on Ohm's and Kirchoff's laws.
The student knows the structures of basic filters and is able to simulate their operation with a simulation tool,

Assessment criteria, excellent (5)

The student will understand and apply the basics of circuits and related laws such as Ohm’s Law and Kirchfoff’s Laws. The student understands the purpose of circuit components and is able to solve complex circuits with a simulation tool and mathematical methods based on Ohm's and Kirchoff's laws.
The student knows and understands the structures and operation of basic filters and is able to design and simulate filters that meet the set requirements with a simulation tool.

Evaluation scale

H-5

Materials

Cisco Networking Academy Web based learning environment. Contents: 0. Course Introcduction 1. Network 2. Network OS 3. Protocols & Communications 4. Network Acces 5. Ethernet 6. Network Layer 7. IP Addressing 8. Subnetting Networks 9. Transport Layer 10. Application Layer 11. Build a Network

Further information

After completing the course, the student will be familiar with the structure of the layered OSI and TCP / IP models, the functionalities of the LAN media, the general cabling standard, the applications of the most common LAN devices and applications, and the key TCP / IP protocols, and will be able to perform IP subnetwork. After completing the course, the student knows how to build and test a small local area network and connect it to a local area network. The student knows how to calculate IP addresses and subnets, and to define IP address book for workstations and to test the functionality of the IP connection.

Evaluation scale

H-5

Assessment methods and criteria

Examination, home excercises
Total exam score under 70% --> Fail (0)
Over 70% --> 1
Over 75%--> 2
Over 80% --> 3
Over 85% --> 4
Over 90% --> 5

Materials

Cisco Networking Academy Web based learning environment. Contents: 0. Course Introcduction 1. Network 2. Network OS 3. Protocols & Communications 4. Network Acces 5. Ethernet 6. Network Layer 7. IP Addressing 8. Subnetting Networks 9. Transport Layer 10. Application Layer 11. Build a Network

Further information

After completing the course, the student will be familiar with the structure of the layered OSI and TCP / IP models, the functionalities of the LAN media, the general cabling standard, the applications of the most common LAN devices and applications, and the key TCP / IP protocols, and will be able to perform IP subnetwork. After completing the course, the student knows how to build and test a small local area network and connect it to a local area network. The student knows how to calculate IP addresses and subnets, and to define IP address book for workstations and to test the functionality of the IP connection.

Evaluation scale

H-5

Assessment methods and criteria

Examination, home excercises
Total exam score under 70% --> Fail (0)
Over 70% --> 1
Over 75%--> 2
Over 80% --> 3
Over 85% --> 4
Over 90% --> 5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

H-5

Assessment criteria, fail (0)

Less than 50% ( 50points ) of the subjects covered in the course are unproven assignments, or alternatively in the learning diary video.

Assessment criteria, satisfactory (1-2)

50-65 points
The student understands the principles of robotics and knows how to use and design simple robotics implementations.
The student is able to implement simple robotics solutions independently.
The student is able to solve basic robotics problems and search for additional information in a guided manner, for example from the digital materials of the Robot Operating System.

Assessment criteria, good (3-4)

65-90 points
The student understands the principles of robotics and knows how to use and plan robotics implementations using a suitable method.
The student is able to implement robotics implementations and solutions independently. The student knows how to use the features offered by robotics actuators and plan a robot implementation. The student knows how to choose the most functional solution for the defined need from among several robotics solutions. The student knows how to implement a working implementation with the selected solution.
The student is able to solve problems and knows how to search for additional information on robotics digital materials.

Assessment criteria, excellent (5)

> 90 points
The student can make robotics applications fluently. The student knows how to choose the solution that best suits the task. The student knows how to apply the opportunities offered by robotics in practice in a versatile way. The student knows how to combine several different practices into a functional whole.

Evaluation scale

H-5

Assessment criteria, fail (0)

Less than 50% ( 50points ) of the subjects covered in the course are unproven assignments, or alternatively in the learning diary video.

Assessment criteria, satisfactory (1-2)

50-65 points
The student understands the principles of robotics and knows how to use and design simple robotics implementations.
The student is able to implement simple robotics solutions independently.
The student is able to solve basic robotics problems and search for additional information in a guided manner, for example from the digital materials of the Robot Operating System.

Assessment criteria, good (3-4)

65-90 points
The student understands the principles of robotics and knows how to use and plan robotics implementations using a suitable method.
The student is able to implement robotics implementations and solutions independently. The student knows how to use the features offered by robotics actuators and plan a robot implementation. The student knows how to choose the most functional solution for the defined need from among several robotics solutions. The student knows how to implement a working implementation with the selected solution.
The student is able to solve problems and knows how to search for additional information on robotics digital materials.

Assessment criteria, excellent (5)

> 90 points
The student can make robotics applications fluently. The student knows how to choose the solution that best suits the task. The student knows how to apply the opportunities offered by robotics in practice in a versatile way. The student knows how to combine several different practices into a functional whole.

Objective

The student is able to utilize the possibilities of cloud computing services in application development. The student has an overview of different cloud computing services and their features. The student is able to choose a suitable cloud computing service, which may be related to data management, image recognition, text conversion, video processing or other cloud computing.

Content

The course covers various aspects of Cloud Computing and usage examples:
- Deployment of a service provider's Cloud Computing solution
- Identify an object from an image using a cloud computing service
- Processing the text and identifying things from the text
- Programming in the cloud computing service
- Data management using a cloud computing service
- Comparison of cloud computing solutions
- Using a solution that utilizes cloud computing on a mobile device

Materials

Materials will be compiled and made available in the Moodle workspace. If necessary, additional resources and materials will be acquired and added from the internet. This includes documentation and guides for the cloud services used in the course.

Self-study prerequisites, if not familiar: Basics of Python: Familiarity with the basic concepts and syntax of the Python programming language. Basics of Data Management: Understanding of fundamental aspects of data handling, including JSON and databases. Basics of Information Technology: Knowledge of key IT concepts, including understanding what a CPU and GPU are.

Teaching methods

Online material. Practical exercise support offered in workshops

Content scheduling

Theory: Introduction to IaaS, PaaS, and other cloud service options.
Basics and introduction to cloud computing.
Cloud computing: Machine learning in the cloud (Google's Teachable Machine: An interactive tool for machine learning, Google Colab, and possibly other tools), focusing on image recognition and natural language processing.
Basics of cloud platforms and cloud deployment.
Introduction to Firebase/Supabase or other similar technologies.
Ethical and sustainable approaches, covering GDPR, energy consumption, and cost savings.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student understands the principles of cloud computing and cloud service and is able to use cloud computing in simple implementations. The student is able to solve basic problems and search for more information from the digital materials of cloud computing service providers.

Assessment criteria, good (3)

The student understands the principles of cloud computing and cloud service and is able to plan and implement implementations that utilize cloud computing.

The student is able to utilize the features of the cloud computing service. The student is able to choose the most effective solution for a defined need from the services of several cloud computing service providers. The student is able to implement a solution that works with the selected service.

The student is able to solve problems and is able to search for more information from the digital materials of cloud computing service providers.

Assessment criteria, excellent (5)

The student is able to use the cloud computing service smoothly as part of an information system. The student is able to choose the most suitable cloud computing solution for the task. The student is able to apply the features of the cloud computing service in many ways. The student is able to utilize the features of the cloud computing service in software development.

Assessment methods and criteria

Grades are based on the quality, quantity, and comprehensiveness of the exercises.

Objective

The student is able to design and implement platform-independent mobile applications, taking into account the differences between different mobile platforms.

Content

- Native Mobile Programming vs. Platform-Independent Mobile Programming
- Different implementations of a platform-independent mobile application
- Development of a platform-independent mobile application with the selected technology
- Platform-independent mobile application development process: finalization, testing and deployment

Location and time

Classroom according to the schedule

Materials

All the necessary study materials for the course will be available on Moodle. In addition to the provided materials, up-to-date resources from the internet will also be utilized.

Teaching methods

In the study module, up-to-date methods and materials are utilized in the teaching of cross-platform mobile programming. During the study module, students will familiarize themselves with different cross-platform mobile programming techniques and methods. At the beginning of the study module, the student chooses the method of completion: the options are a project-based approach, focusing on a specific cross-platform technology to deepen skills with the chosen technique, or alternatively, completing smaller exercises throughout the study module that cover multiple different cross-platform mobile programming techniques.

Completion alternatives

To be negotiated separately with the course instructor. Possibility for recognition of prior learning.

Content scheduling

Basics of cross-platform mobile development
Introduction to cross-platform mobile development with chosen technology
Programming language of chosen technology
Setting up the environment
First cross-platform mobile application
Best practices with chosen technology
Problem with cross-platform development - platform specific code
Testing of cross-platform mobile application
Deployment to production

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is familiar with various options for implementing a platform-independent mobile application and is able to implement simple mobile applications with the chosen technology under supervision.

Assessment criteria, good (3)

The student is able to independently design and implement functional platform-independent mobile applications and is able to independently search for and apply external information sources in development work.

Assessment criteria, excellent (5)

The student is able to independently design and implement challenging platform-independent mobile applications and to make effective use of testing and optimization tools in the finalization of a mobile application.

Assessment methods and criteria

The study module is assessed based on exercises, using a scale of 0-5

Objective

The objective of a Climatic and Reliability Testing course is to provide you an understanding of the principles, methods and techniques for testing the performance of products and systems under various environmental conditions and to assess their reliability under normal and extreme conditions. This course aims to equip you with the knowledge and skills needed to perform climatic and reliability testing, understand the results, and use that information to make informed decisions about product design and development. The goal is to provide you with an understanding of how to perform tests that mimic real-world conditions and to use that information to improve the reliability and performance of products in the field.

Content

Introduction to Climatic and Reliability Testing: Definition, importance, and applications of climatic and reliability testing.

Environmental Testing: Overview of environmental testing, including temperature, humidity, vibration, shock, and altitude testing.

Reliability Testing: Overview of reliability testing, including statistical methods, life testing, accelerated life testing, and stress testing.

Test Equipment and Methods: Overview of test equipment and methods, including test chambers, temperature and humidity controls, and data acquisition systems.

Test Planning and Design: Overview of test planning and design, including selection of test conditions, sample size, and test duration.

Data Analysis and Reporting: Overview of data analysis and reporting, including statistical methods, data presentation, and interpretation of results.

Environmental and Reliability Standards: Overview of environmental and reliability standards, including industry and international standards.

Case Studies: Overview of case studies of successful climatic and reliability testing, including lessons learned and best practices.

Future Trends and Challenges: Overview of future trends and challenges in climatic and reliability testing, including new technologies and emerging trends.

The course may include hands-on laboratory exercises and projects to give students practical experience in performing climatic and reliability tests

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

Knows reasons to do climatic and reliability testing.
- Standards to consider
- General features of the typical climatic tests
- Simulation vs. field testing

Can demonstrate and understand the concepts of reliability engineering.

Assessment criteria, good (3)

Is confident with:
- Reasons to do climatic and reliability testing
- Determine a life test, estimate reliability values from the test data, and set confidence limits on the results.

Assessment criteria, excellent (5)

Is able to:
- Understand Climatic and Reliability Engineering in Business
- Manage Data to Business Case Justification
- Understands the Criticality and Risk
- Understands Life Cycle Considerations
- Can do Root Cause Analysis
- Manage a climatic and reliability testing project

Evaluation scale

H-5

Materials

Cisco Networking Academy Web based learning environment. Contents: 0. Course Introcduction 1. Network 2. Network OS 3. Protocols & Communications 4. Network Acces 5. Ethernet 6. Network Layer 7. IP Addressing 8. Subnetting Networks 9. Transport Layer 10. Application Layer 11. Build a Network

Further information

After completing the course, the student will be familiar with the structure of the layered OSI and TCP / IP models, the functionalities of the LAN media, the general cabling standard, the applications of the most common LAN devices and applications, and the key TCP / IP protocols, and will be able to perform IP subnetwork. After completing the course, the student knows how to build and test a small local area network and connect it to a local area network. The student knows how to calculate IP addresses and subnets, and to define IP address book for workstations and to test the functionality of the IP connection.

Evaluation scale

H-5

Assessment methods and criteria

Examination, home excercises
Total exam score under 70% --> Fail (0)
Over 70% --> 1
Over 75%--> 2
Over 80% --> 3
Over 85% --> 4
Over 90% --> 5

Evaluation scale

H-5

Materials

Cisco Networking Academy Web based learning environment. Contents: 0. Course Introcduction 1. Network 2. Network OS 3. Protocols & Communications 4. Network Acces 5. Ethernet 6. Network Layer 7. IP Addressing 8. Subnetting Networks 9. Transport Layer 10. Application Layer 11. Build a Network

Further information

After completing the course, the student will be familiar with the structure of the layered OSI and TCP / IP models, the functionalities of the LAN media, the general cabling standard, the applications of the most common LAN devices and applications, and the key TCP / IP protocols, and will be able to perform IP subnetwork. After completing the course, the student knows how to build and test a small local area network and connect it to a local area network. The student knows how to calculate IP addresses and subnets, and to define IP address book for workstations and to test the functionality of the IP connection.

Evaluation scale

H-5

Assessment methods and criteria

Examination, home excercises
Total exam score under 70% --> Fail (0)
Over 70% --> 1
Over 75%--> 2
Over 80% --> 3
Over 85% --> 4
Over 90% --> 5

Evaluation scale

H-5

Location and time

Teaching takes place between weeks 2 and 17. There are 4 hours of lessons per week.

Materials

All study material is offered in the course workspace.

Teaching methods

Teaching is carried out as face-to-face teaching. Studying takes place in a laboratory, where students do laboratory work under supervision and independently produce reports to be evaluated for practice tasks.

Exam schedules

There is no exam in the course, but the course is completed with practice assignments. When renewing a study course, raising a grade, and raising a failed grade as accepted, the valid diploma rules of the Lapland University of Applied Sciences are followed.

Completion alternatives

Other methods of completion of the study course are agreed separately with the teacher responsible for the study course.

Content scheduling

The course takes place between the 3rd and 16th of the calendar weeks. The last day to return the exercises for the course is 30 April 2025.

Evaluation scale

H-5

Assessment methods and criteria

The evaluation is based on the returned exercises, which are scored. A maximum of approx. 33% of the total score is required for a grade of 1 in the course. A maximum of 85% of the total score is required for a grade of 5.

Assessment criteria, fail (0)

The student does not reach the minimum requirements set for the course.

Assessment criteria, satisfactory (1-2)

The student is able to select and implement a sensor or actuator as part of an IoT or automation system.

Assessment criteria, good (3-4)

The student masters the operating principles of sensors and actuators and is able to independently implement the connection of sensors and actuators to an IoT or automation system.

Assessment criteria, excellent (5)

The Student able to plan and implement the electrotechnical installation of measurement sensing and actuators and galvanic separation in a disturbed environment.

Location and time

Teaching takes place between the 3rd and 176h of the study weeks. The course ends at the end of the semester on July 31, 2024. The last return date for the course exercises is, April 30, 2025

Materials

The study course material is offered in the study course workspace.

Teaching methods

Teaching is mainly face-to-face teaching. The course is completed with exercises done in the laboratory. Students produce reports from the exercises independently, which are returned to the workspace used for the course.

Exam schedules

There is no exam in the course. The current guidelines of Lapland AMK apply to renewing the study course and raising the grade.

Completion alternatives

The course can be completed in an alternative way by agreeing with the teacher responsible for teaching the course. The current guidelines of Lapland AMK apply to the identification of previously acquired skills (AHOT).

Content scheduling

The course is completed between the 3rd and 177h of the study weeks.

Evaluation scale

H-5

Assessment methods and criteria

The course is evaluated on a scale of 0 (Fail) to 5 (Commendable). The practice tasks of the course are scored and the passing limit is a maximum of 33% of the maximum score. The limit of a commendable grade is approx. 90% of the maximum score.

Assessment criteria, fail (0)

The student does not reach the minimum requirements set for the course.

Assessment criteria, satisfactory (1-2)

The student understands the basics of wireless data transmission and applies the principles in practice.

Assessment criteria, good (3-4)

The student knows how to choose a suitable standard and technology for wireless data transmission. The student is able to implement a wireless data transfer application in a controlled manner.

Assessment criteria, excellent (5)

The student can plan and implement wireless network solutions independently, taking information security requirements into account.

Evaluation scale

H-5

Evaluation scale

H-5

Objective

The student is able to utilize the possibilities of cloud computing services in application development. The student has an overview of different cloud computing services and their features. The student is able to choose a suitable cloud computing service, which may be related to data management, image recognition, text conversion, video processing or other cloud computing.

Content

The course covers various aspects of Cloud Computing and usage examples:
- Deployment of a service provider's Cloud Computing solution
- Identify an object from an image using a cloud computing service
- Processing the text and identifying things from the text
- Programming in the cloud computing service
- Data management using a cloud computing service
- Comparison of cloud computing solutions
- Using a solution that utilizes cloud computing on a mobile device

Materials

Materials will be compiled and made available in the Moodle workspace. If necessary, additional resources and materials will be acquired and added from the internet. This includes documentation and guides for the cloud services used in the course.

Self-study prerequisites, if not familiar: Basics of Python: Familiarity with the basic concepts and syntax of the Python programming language. Basics of Data Management: Understanding of fundamental aspects of data handling, including JSON and databases. Basics of Information Technology: Knowledge of key IT concepts, including understanding what a CPU and GPU are.

Teaching methods

In-person teaching and support for exercises during classes, as well as online materials to support the completion of tasks.

Content scheduling

Theory: Introduction to IaaS, PaaS, and other cloud service options.
Basics and introduction to cloud computing.
Cloud computing: Machine learning in the cloud (Google's Teachable Machine: An interactive tool for machine learning, Google Colab, and possibly other tools), focusing on image recognition and natural language processing.
Basics of cloud platforms and cloud deployment.
Introduction to Firebase/Supabase or other similar technologies.
Ethical and sustainable approaches, covering GDPR, energy consumption, and cost savings.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student understands the principles of cloud computing and cloud service and is able to use cloud computing in simple implementations. The student is able to solve basic problems and search for more information from the digital materials of cloud computing service providers.

Assessment criteria, good (3)

The student understands the principles of cloud computing and cloud service and is able to plan and implement implementations that utilize cloud computing.

The student is able to utilize the features of the cloud computing service. The student is able to choose the most effective solution for a defined need from the services of several cloud computing service providers. The student is able to implement a solution that works with the selected service.

The student is able to solve problems and is able to search for more information from the digital materials of cloud computing service providers.

Assessment criteria, excellent (5)

The student is able to use the cloud computing service smoothly as part of an information system. The student is able to choose the most suitable cloud computing solution for the task. The student is able to apply the features of the cloud computing service in many ways. The student is able to utilize the features of the cloud computing service in software development.

Assessment methods and criteria

Grades are based on the quality, quantity, and comprehensiveness of the exercises.

Objective

The student knows the basics of the organization's information security work and the standards used. The student acquires the skills for information security development work in his own organization. The student knows the ethical aspects related to information security and data protection. The student is able to adapt to the rapid changes in the information security industry and maintain his skills.

Content

Introduction to information security, assessment of information security risks
Developing information security in companies, incl. required documents
The organization's information security by sub-areas
Data protection, EU data protection regulation and other legislation

Materials

Materials will be presented in Moodle Workspace

Teaching methods

Lessons and seminars

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is able to identify key security threats. The student is able to act in such a way that he / she does not pose a security threat to his / her organization.

Assessment criteria, good (3)

Opiskelija osaa ottaa huomioon lainsäädännön asettamat vaatimukset organisaation tietoturvalliselle toiminnalle. Opiskelija osaa laatia organisaatiolleen ohjeistuksen hyvistä tietoturvakäytännöistä.

Assessment criteria, excellent (5)

The student knows how to act proactively and take into account matters affecting the organization's information security in the national and international operating area, and instructs the operation of her own organization so that information security is part of the way the organization operates.

Assessment methods and criteria

Grading will be based on active partisipating in lectures and excersies.
Submitting papers and delivering persentations.

Assessment criteria, fail (0)

No partisipating and no completed tasks or excersises

Assessment criteria, satisfactory (1-2)

The student gains a good view of Cyber security in the field of Machine learning and has good abilities to further his/ her expertise. The majority of tasks given are completed

Assessment criteria, good (3-4)

The student gains a great view of Cyber security in the field of Machine learning and has great abilities to further his/ her expertise. The majority of tasks given are completed.

Assessment criteria, excellent (5)

The student gains a excellent view of Cyber security n the field of Machine learning and has excellent abilities to further his/ her expertise. All tasks given are completed.

Objective

The student is able to design and implement platform-independent mobile applications, taking into account the differences between different mobile platforms.

Content

- Native Mobile Programming vs. Platform-Independent Mobile Programming
- Different implementations of a platform-independent mobile application
- Development of a platform-independent mobile application with the selected technology
- Platform-independent mobile application development process: finalization, testing and deployment

Location and time

Zoom classroom according to the schedule

Materials

All the necessary study materials for the course will be available on Moodle. In addition to the provided materials, up-to-date resources from the internet will also be utilized.

Teaching methods

In the study module, up-to-date methods and materials are utilized in the teaching of cross-platform mobile programming. During the study module, students will familiarize themselves with different cross-platform mobile programming techniques and methods. At the beginning of the study module, the student chooses the method of completion: the options are a project-based approach, focusing on a specific cross-platform technology to deepen skills with the chosen technique, or alternatively, completing smaller exercises throughout the study module that cover multiple different cross-platform mobile programming techniques.

Completion alternatives

To be discussed separately with the course instructor. Possibility for recognition of prior learning.

Content scheduling

Basics of cross-platform mobile development
Introduction to cross-platform mobile development with chosen technology
Programming language of chosen technology
Setting up the environment
First cross-platform mobile application
Best practices with chosen technology
Problem with cross-platform development - platform specific code
Testing of cross-platform mobile application
Deployment to production

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is familiar with various options for implementing a platform-independent mobile application and is able to implement simple mobile applications with the chosen technology under supervision.

Assessment criteria, good (3)

The student is able to independently design and implement functional platform-independent mobile applications and is able to independently search for and apply external information sources in development work.

Assessment criteria, excellent (5)

The student is able to independently design and implement challenging platform-independent mobile applications and to make effective use of testing and optimization tools in the finalization of a mobile application.

Assessment methods and criteria

The study module is assessed based on exercises, using a scale of 0-5

Evaluation scale

H-5

Evaluation scale

H-5

Evaluation scale

Approved/Rejected

Evaluation scale

H-5

Evaluation scale

H-5