The course introduces students to some fundamentals of research methodology. The course comprises a series of lectures which cover the following topics: Philosophy of Science, Quantitative Research Methods, Qualitative Research Methods, Basic Machine Learning Methods, Theoretical Research Methods, How to find a Research Topic, Literature Analysis, Reading and Reviewing Papers, Research Ethics and Commercialising Research. The lectures will be complemented by a series of workshops, labs and assignments that require students to do some small research focused tasks that help them get a hands-on experience of research, both individually and in teams of students. This includes different tasks such as topic modelling, statistical analysis, applying different machine learning techniques to solve a problem in a team, proving theorems, complexity analysis, designing a research project, reviewing papers and presenting papers. Workshops cover topics such as research integrity, time management and project management, teamwork, reading strategies, report writing, and presenting research. At the end of the course, students will be confident to start working on their own research projects.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Demonstrate an ability to communicate in relation to a computing project in oral, written and graphical forms, with an an appreciation of the need to pitch any communication item appropriately for the audience. This includes demonstrated skills in the writing of abstracts and research papers.
- Understanding of the process of identifying and formulating research problems.
- Ability to carry out literature searches and some ability to critically evaluate literature.
- Design and conduct experiments, devise appropriate measurements, analyze and interpret data and form reliable conclusions.
- Understanding of academic integrity and the importance of building upon and correctly attributing the work of others.