Project: Data Analytics and Visualization (5 cr)
Code: R504D99-3001
General information
Enrollment
03.10.2022 - 15.01.2023
Timing
16.01.2023 - 18.05.2023
Credits
5 op
Mode of delivery
Contact teaching
Unit
Bachelor of Engineering, Information Technology
Teaching languages
- English
Seats
0 - 30
Degree programmes
- Machine Learning and Data Engineering
Teachers
- Jyri Kivinen
- Aku Kesti
- Tuomas Valtanen
- Maisa Mielikäinen
- Tanja Kyykkä
Responsible person
Maisa Mielikäinen
Student groups
-
R54D22S
Objective
The student is able to perform data analytics and visualization tasks in a real project.
The student is familiar with the necessary tools and technologies for data analysis and visualization.
The student knows the basics of project management. The student is able to work on a project and produce the main documentation of the project. The student is able to work in a team to achieve a common goal. The student knows project communication. The student is able to perform in various project-related situations.
Content
Basics of project management: process and documentation.
The project includes 1 ECTS of communication.
Location and time
The theoretical introduction to the subject mainly takes place before the ski holiday and the practical project is started after it. Learning mainly takes place on campus according to the timetable. The reviews are carried out via Teams.
Materials
The lecture material (videos) is provided in Moodle, as well as the document templates needed for the practical project.
Teaching methods
At first, the students familiarize themselves with the project management online material provided in Moodle and complete the tasks related to the material.
After that, for the practical project, students are formed into project groups of 3-4 people who implement an real-world problem-solving project utilizing basics of project management methods. Learning includes e.g. guest lectures on the topic, screenings and guidance sessions. The outputs of the projects will be presented at the joint project exhibition day with all ICT engineering student groups at the end of April.
Completion alternatives
The course can also be completed in a working life project. The method of implementation will be separately agreed in detail with the responsible teacher.
Evaluation scale
H-5
Assessment methods and criteria
Project Management:
The first objective, the student knows the basics of project management and understands the meaning and benefit of their application, is
demonstrated with the accepted tasks (quizzes) in Moodle. This is mandatory for everyone.
The rest of the competences are demonstrated in practical project:
- Skills of problem-solving
- Quality of the documentation
- Skills to manage projects in different situations
- Student commitment and activity
Communication:
Assessment criteria, fail (0)
The student is absent and does not actively participate in the project. A very passive or negative attitude can also lead to rejection from the project team as well as failing grade.
Assessment criteria, satisfactory (1-2)
The student knows how to implement data analytics and visualization tasks supported in a real project without taking the main responsibility for tasks that require problem solving. The student understands the importance of the tools and techniques needed for data analysis and visualization, but is not yet capable of fully applying them. The student knows how to work in a project and produce the main project documentation. The student is mainly and does not usually present constructive solutions that support reaching the goal.
Assessment criteria, good (3-4)
The student knows how to implement data analytics and visualization tasks in a real project. The student demonstrates good competence in applying the tools and techniques needed for data analysis and visualization. The student knows the basics of project management and understands the meaning and benefit of their application. The student knows how to work in a project and produce the main project documentation. The student knows how to work actively in a group, in a constructive spirit, and takes others into account in order to achieve a common goal.
Assessment criteria, excellent (5)
The student is able to perform data analytics and visualization tasks in a real project in a wide-ranging and versatile manner. The student demonstrates extensive competence in applying the tools and techniques needed for data analysis and visualization. The student knows how to work in a project and produces high-quality main project documentation. The student knows how to work in a group actively, in a constructive spirit, and consider others in order to achieve a common goal.