Welcome!

This website aims to provide a high-level overview of important academic skills.
(with an emphasis on education and research in machine learning and artificial intelligence)

Many academic skills are implicitly taught. How do you study course material? How do you write equations? How do you structure a research paper? How do you approach a research/thesis project? These topics are discussed in certain skill courses, but you also gradually learn them over the years, through feedback from your supervisor, by watching other students around you, or simply through trial and error.

Idea
What students in my experience often lack is a condensed overview of these skills, in the form of a reference guide where they can quickly check back. This website aims to fill this gap. It tries to summarize what I learned myself over the years, on studying and doing research, in a relatively condensed form. Do note that it is just my advice, and thereby not set in stone: always check with your own teacher/supervisor whether they agree with a certain idea. 

Target audience
This website is intended for bachelor, master (and PhD) students. We will not discuss any technical topics, but only focus on general academic skills. However, there is an emphasis on education and research in computer science, specifically focusing on machine learning and artificial intelligence. Most pages have a much wider applicability, but certain pages are only for exact sciences (such as Equations) or even only for machine learning (such as Hyperparameter Tuning).

Structure
The website is structured around the most important aspect of education and research: 1) reading, 2) experimenting, 3) writing and 4) thesis/research project management. The top of each page indicates for which audience the material is intended. In general: 

• As a bachelor course student, consider: 

• • Reading: Studying course material, Studying Equations

  • Experimenting: Experimental design, Hyperparameter tuning,  Statistical practice

  • Writing: General Advice, Course report structure, Equations, Figures & Tables 

  • Presenting: General advice, Preparing a story, Preparing slides, Presenting, Handling questions 

• For a master course, add to the above: 

• • Experimenting: Computational feasibility, Software 

  • Writing: References 

• As a  thesis (BSc/MSc/PhD) student, add to the above: 

• • Reading: Reading a research paper, Finding related work 

  • Thesis: Finding a thesis topic, Thesis process, Work Approach, Supervisor meetings, Templates

You should be able to browse through all content in roughly ~1-2 hours. 

Hope you find the website useful. I'd be very happy to get feedback, for which you can always email me: t.m.moerland (at) liacs.leidenuniv.nl

Good luck!