Nowadays, data science is not restricted only to the tech giants, but is already used by organizations across many industries, from FMCG to the financial services. Although the exact data science process varies depending on the specific use case, there is a common framework that is used to deliver data…

In a famous study, it was shown that beliefs (i.e. expectations) can actually bring about the expected behaviour, creating a reality. A famous example: people who expect to die young may smoke and take drugs, ending up dying young in reality. …

On its own, agile is more of a mindset, and there are several established frameworks that one can adopt to achieve agility.

The two most popular methods to achieve agile principles are Kanban and Scrum. Kanban (Japanese: 看板) is used to to manage a continous queue of work items, which…

Agile is a continuous learning approach that concerns two aspects: project management and product development. In particular, it is an approach to managing projects that avoids expensive upfront planning while reducing complexity and minimizing risk. Agile methods are traditionally applied in software development and IT support (e.g. service ticketing).

Some…

In summary:

1. Clarify the problem
2. Generate inputs and/or outputs
3. Create test cases
4. Plan your program
5. Code
6. Analyse the performance: speed/runtime
7. Debug

Step 1: Clarify the problem to be solved. This is important to make sure that you do not spend wasted effort on solving something that the interviewer is not…

This post is targeted mainly at computer scientists, statisticians, engineers, physicists, data scientists, mathematicians, and any other professionals in a (esp. scientific) discipline who are interested in consuming the state-of-the-art literature in biology and medicine. Since lots of texts in biomedicine often use heavy jargons, non-biologists usually find it quite…