PENG9560 Topics in Artificial Intelligence and Machine Learning Emneplan

On successful completion of the course, the student has the following learning outcomes classified as knowledge, skills and competence:

Knowledge

The student can

• analyze and critically assess the scientific work of others

Skills

The student can

• demonstrate working knowledge of the ethical and technical principles that govern scientific research and publication, including international citation and reference standards
• demonstrate that they can conduct a supervised research project in accordance with research ethics guidelines and regulations, and guidelines from relevant governmental bodies (i. e. The Norwegian Data Protection Authority, relevant Norwegian Research Ethics Committees)
• choose and apply relevant methods of data collection for research or scientific inquiry
• write a thesis according to criteria determined by the university
• write a thesis according to the APA 7th standard and other reporting standards
• critically assess the results of his or her own work
• critically assess various sources of information

Competence

The student can

• participate in the development of the behavioral sciences
• justify their professional behavior with reference to ethical guidelines, general ethical considerations and their own assessment of the situation
• analyze and critically assess various sources of information with relevance for the thesis.

Basic background in statistics or probability theory. Knowledge of a programming language.

The course includes seminars on research ethics, how to write a project outline, and requirements for the master thesis.

Otherwise the thesis outline and thesis are individual works. Submission of thesis outline is required before a supervisor is appointed. Thesis outline must be submitted the semester before thesis submission at the latest. Students are advised to conduct their project in collaboration with researchers at the department.

Thesis supervision is compulsory. Each candidate gets a maximum of 30 hours of supervision during the thesis work, supervisor preparation included. If a non-faculty supervisor is appointed, resources are divided by 2/3 of the time for the main supervisor and 1/3 for the internal second supervisor.

The course is structured in five modules:

• Module 1: Unsupervised Data Mining
• Module 2: Supervised Machine Learning
• Module 3: Reinforcement Learning
• Module 4: Artificial Neural Network and Deep Learning
• Module 5: Major Concepts in Artificial Intelligence, including: complex systems (networks, cellular automata, and agent-based models) and evolutionary computing

The following required coursework must be approved before the student can take the exam:

a. Research ethics seminar 1 and 2 must be fully attended.

b. Approved thesis outline.

c. A signed contract with the appointed supervisor.

Thesis. Submission of master’s thesis according to program specifications, consisting of 1 scientific article. Technical standards according to the current APA manual. Submitting dates each year: June 15th and November 15th.

Thesis format

The 40 ECTS Master’s thesis consists of one article written in accordance with the author guidelines specified in the current APA Publication Manual. The length should be appropriate for the work that is reported, but should commonly not exceed 40 pages, including the title page, references, tables, and figures, but excluding appendices.

Ethics and data protection

An account of ethical considerations is regardless of thesis format. A risk -and vulnerability analysis (ROS-vurdering) should normally be conducted if the thesis includes empirical data on humans or nonhuman animals, and a case number should be provided when handing in the thesis. If data on humans are included in the thesis, an account of data protection issues is typically required. The description of ethical and data protection considerations can be included in the main body of the thesis. If the decision is made that such an account is unnecessary to include in the main body of the thesis, a reflection note on this topic should be attached to the thesis. A reflection note is a short description of ethical and data protection considerations, maximum 6000 characters, including spaces. For theses that do not include empirical data, research ethics relevant to the thesis should be discussed, either in the main body of the text or a reflection note.

Some Master projects may require consideration or approval from external bodies, such as Norwegian Centre for Research Data (NSD), the Regional Committee for Medicine and Health Sciences Research Ethics (REK), National Committee for Research Ethics in the Social Sciences and the Humanities (NESH), and/or internal or external data protection officials. It is ultimately the responsibility of the main supervisor or, if the main supervisor is external, the supervisor at OsloMet, to ensure that the relevant bodies are consulted. If external bodies are consulted, a case number should be provided when handing in the thesis. If a decision is made that there is no need to consult external bodies regarding ethics or data protection, a description of the deliberations preceding this decision is required, either in the main body of the thesis or in the reflection note. If the thesis is an empirical work, the main supervisor must state in writing that the research is conducted in accordance with current laws and regulations before the thesis can be submitted.

All.

Grade scale A-F

One internal and one external examiner will assess each exam.

Two internal examiners. External examiner is used periodically.