Programplaner og emneplaner - Student
TRE1400 Fysikk - 3-terminsordning Emneplan
- Engelsk emnenavn
- Physics - Preparatory course
- Studieprogram
-
Bachelorstudium i ingeniørfag - byggBachelorstudium i ingeniørfag - dataBachelorstudium i ingeniørfag - elektroBachelorstudium i ingeniørfag - energi og miljø i byggBachelorstudium i ingeniørfag - bioteknologi og kjemiBachelorstudium i ingeniørfag - maskinIngeniørutdan. - 3 terminsordning
- Omfang
- 0.0 Forkurspoeng
- Studieår
- 2024/2025
- Pensum
-
HØST 2024
- Timeplan
- Programplan
-
- Emnehistorikk
-
Innledning
Prerequisite knowledge
Students must be registered in the third year and have completed at least 100 credits from the first and second years by 1 October before they are assigned a topic for their bachelor’s thesis.
Requirement for preliminary project
A project outline (separate form) must be approved by 15 November. It is the students’ responsibility to:
- form project groups consisting of four members
- contact an enterprise and agree on a collaboration for the bachelor’s thesis
- define a research question and a draft solution for the bachelor’s thesis
Forkunnskapskrav
After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge
The student:
- is capable of using and further developing their knowledge and expertise from several of the subject areas in the bachelor’s degree programme to carry out a realistic engineering assignment
Skills
The student:
- is capable of planning and carrying out a large-scale project in the field
- is capable of leading project meetings and communicating solutions both orally and in writing
- has practical experience of the basic principles behind scientific work methods, including searching for, assessing and using specialist literature and writing a scientific report
- is capable of searching for and assessing relevant specialist literature and writing the theoretical part of a scientific report based on this material
General competence
The student:
- is capable of translating knowledge into practical solutions
- is capable, in an independent and systematic manner, of carrying out an engineering assignment based on a practical industrial or research-related issue
- is capable of communicating electronic engineering and information technology knowledge both orally and in writing, in both Norwegian and English
- masters both independent work and team work, including the planning and implementation of a large-scale engineering project
- demonstrates a responsible and ethical approach in their professional expertise
Læringsutbytte
The assignment of bachelor’s theses is based on the guidelines applicable to the faculty and the study programme. The thesis is preferably written in cooperation with a business or research community. A supervisor from the study programme will be appointed. For projects carried out in cooperation with an enterprise or public agency, an external supervisor will also be appointed.
Arbeids- og undervisningsformer
The following coursework is compulsory and must be approved before the student can sit the exam:
- two lectures (start-up and report writing)
- preliminary project (a project outline must be completed prior to 15th of November)
- one meeting with the course coordinator
- one oral presentation
Students may be required to write the thesis in English.
Arbeidskrav og obligatoriske aktiviteter
The assessment of the group bachelor’s thesis (4 students) will be based on the execution of the project, the report, the poster and the oral presentation.
- The execution, oral presentation with demo video and poster in English count 40% and are assessed on the basis of the project’s degree of difficulty, the students’ planning and progress, initiative, assessment ability and independence, and the supervisor/client’s benefit from the project.
- The report counts 60% and is assessed on the basis of the students’ understanding of the issue at hand, the thoroughness of the documentation, the discussion, critical assessment, clear presentation, systematic structure, literary references and degree of independence in the writing process. The entire group is given one common grade on the report.
Only the grade given for the report can be appealed. The grade given for the execution and oral presentation cannot be appealed. There will be a possibility for an individual marking on the oral part.
All parts of the exam must be awarded grade E or better for the student to pass the course.
Vurdering og eksamen
After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and competence:
Knowledge
The student:
- has a basic technological understanding of the most important concepts in machine learning, data science and artificial intelligence
- has knowledge of the most important methods in machine learning, data science and artificial intelligence
- has knowledge of platforms that can be used to complete major data science projects (for instance IBM Watson’s cloud services)
Skills
The student:
- masters basic data science tools and can extract and visualise information from large quantities of data
- understands the workflow in bigger data science, artificial intelligence or machine learning projects
- is capable of using open-source and commercial tools that are used in industrial projects in the fields of data science, machine learning or artificial intelligence
General competence
The student:
- masters methods and tools used to develop and carry out projects in data science, machine learning or artificial intelligence
- is familiar with the different methods that are used to find the right tools to carry out data science projects
- has an overview of how to visualise and manipulate data and how to develop predictive methods for solving industry problems and other issues relevant to working life
Hjelpemidler ved eksamen
Regular follow-up of the project work by a project supervisor.
The students will work in groups of three to five students to complete a project in data science, machine learning or artificial intelligence in cooperation with relevant external parties such as companies or public organisations.
The supervisor(s) can suggest suitable online courses in AI and data science that the students can take during the first few weeks of the course. The students are also encouraged to take other courses (https://cognitiveclass.ai) that will be useful in order to carry out the chosen project assignment. These courses may, among other things, deal with the following areas: Blockchain, the Internet of Things, Chat Bots, advanced use of data science, etc.
The course can be carried out individually by agreement with the course coordinator.
Projects are selected/distributed at the start of the semester.
Vurderingsuttrykk
The course builds on computer science courses from the first year of the programme.
Sensorordning
Written project report (100% of the final grade).
A written project report delivered at the of the semester, individual or in groups (max 5 students), 3000 words +/-10 %.
For group projects, all members of the group receive the same grade. Under exceptional circumstances, individual grades can be assigned at the discretion of the project supervisor(s) and Head of Studies.
The exam result can be appealed.