General scope:
- Aimed at researchers of different backgrounds
- Assume no prior experience with Python (and perhaps not much experience in programming at all)
- Focus on the programming aspect of the language, not on data science toolkit (e.g. pandas, seaborn, etc. - this is covered elsewhere)
Might be nice to structure the course around an end goal that feels useful, relevant, but also non-trivial without using a programming language.
At the end of the course participants should have written a small program to achieve that task.
Some ideas of what this end goal could be:
- Text processing task, which will involve working with files, text manipulation, dictionaries, etc. For example extracting information from paper abstracts (e.g. find how many times disease X is mentioned together with drug Y), taking consideration of synonyms, abbreviations, lower/upper case, etc.
- Running simulations, which may involve defining object classes, methods, etc.
Ideally, it would be good to have two examples for each of these cases (text processing and simulation), as it would allow to have an example to use in the slides and demonstrations and another example that could be used for a capstone project at the end.
General scope:
Might be nice to structure the course around an end goal that feels useful, relevant, but also non-trivial without using a programming language.
At the end of the course participants should have written a small program to achieve that task.
Some ideas of what this end goal could be:
Ideally, it would be good to have two examples for each of these cases (text processing and simulation), as it would allow to have an example to use in the slides and demonstrations and another example that could be used for a capstone project at the end.