ACIT4530 Data Mining at Scale: Algorithms and Systems Course description

Elective specialisation subject.

This course addresses various aspects concerning the relations between literature and society, reading and the book market on the one hand and questions of democracy, participation and cultural policy on the other. The course covers a broad range of empirical and theoretically oriented subjects, contemporary as well as historical perspectives including the following topics: Democracy and citizenship, the digitization and remediation of literature, the globalization of literature and the gendering of literature.

It is an advantage to have some experience with the following subjects:

• Mathematical Analysis
• Basic programming, such as scripting
• Statistics, specifically probability theory

No prerequisites.

The student should have the following outcomes upon completing the course:

Knowledge

Upon successful completion of the course, the student:

• has a deep understanding of how data mining can be used to extract knowledge from data sets.
• has advanced knowledge of the different data mining algorithms.
• should be able to use data mining systems to mine data.

Skills

Upon successful completion of the course, the student:

• can design and implement data mining algorithms
• can deploy different data mining systems and configure them
• can utilize a specialized library for data mining

General competence

Upon successful completion of the course, the student:

• can analyse data mining solutions with regard to robustness and in relation to his/her intended tasks
• can explain how data mining can be used in different applications areas such as business analytics

• Data streaming systems
• Data mining systems and BigData platforms
• Data stream processing methods, such as, but not limited to, anomaly detection, clustering, association rule learning
• Data visualization
• Statistical analysis on large data sets
• Linear algebra applied on BigData
• Using programming to implement analysis and toolchaining

The subject is organised as two seminars, including lectures and presentations. The subject provides a running consideration of research projects presented by the candidates and experienced researchers. Projects are presented in accordance with fundamental academic questions and current international research in the academic area.

No coursework requirements.

Candidates should write an essay of approximately 15 pages based on a subject of their own choice. The essay is to be presented and discussed in one of the seminars. The essay should be completed and handed in within 2 months after the subject is concluded.

All aids allowed as long as source reference and quotation technique requirements are applied.

Approved/not approved.

The essay will be assessed by the course coordinator.

This course is primarily aimed at PhD candidates admitted to the PhD programme in Library and Information Science at OsloMet, but is also open to other applicants who wish to be qualified for research in the field. Admission requirements are a completed "hovedfag", master's degree (120 credits) or equivalent qualification within the same academic area.