Reshape introduction and welcome episodes

[n400peanuts]

This PR solves issue #24 . The introduction and welcome part have been simplified and redundant info has been cut. This has resulted into an effective merge of the intro and welcome into a single episode. Moreover, this episode now introduces immediately an exercise to kick-off the course in a good vibe.

Note that the dataset part is still not completed, as transformers and LLM episodes are still in development and their datasets are not finalised yet.

[github-actions]

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🤖 This automated message can help you check the rendered files in your submission for clarity. If you have any questions, please feel free to open an issue in {sandpaper}.

If you have files that automatically render output (e.g. R Markdown), then you should check for the following:

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Rendered Changes

🔍 Inspect the changes: https://github.com/esciencecenter-digital-skills/Natural-language-processing/compare/md-outputs..md-outputs-PR-26

The following changes were observed in the rendered markdown documents:

 00-welcome.md                              | 63 +++++++++++++------
 01-introduction.md (gone)                  | 97 ------------------------------
 02-preprocessing.md => 01-preprocessing.md |  0
 03-embeddings.md => 02-embeddings.md       |  0
 config.yaml                                |  5 +-
 md5sum.txt                                 |  9 ++-
 6 files changed, 49 insertions(+), 125 deletions(-)

What does this mean?

If you have source files that require output and figures to be generated (e.g. R Markdown), then it is important to make sure the generated figures and output are reproducible.

This output provides a way for you to inspect the output in a diff-friendly manner so that it's easy to see the changes that occur due to new software versions or randomisation.

⏱️ Updated at 2024-09-10 12:50:39 +0000

[svenvanderburg]

Nice changes! I left some small comments here and there.

You could consider moving the welcome to index.md, similar to: https://github.com/carpentries-incubator/deep-learning-intro/blob/2edad370a4e1639f57804324e398b8762cb9a11a/index.md?plain=1#L2 which is rendered like this.

You could also consider adding a prerequisites box like in that lesson, but maybe that already exists somewhere in your lesson or is planned in an issue.

[svenvanderburg]

Suggested change

Natural language processing (NLP) is an area of research and application that focuses on making natural (i.e., human) language accessible to computers so that they can be used to perform useful tasks. Research in NLP is highly interdisciplinary, drawing on concepts from computer science, linguistics, logic, mathematics, psychology, etc. In the past decade, NLP has evolved significantly with advances in technology to the point that it has become embedded in our daily lives: automatic language translation or chatGPT are only some examples.

Natural language processing (NLP) is an area of research and application that focuses on making natural (i.e., human) language accessible to computers so that they can be used to perform useful tasks. Research in NLP is highly interdisciplinary, drawing on concepts from computer science, linguistics, logic, mathematics, psychology, etc. In the past decade, NLP has evolved significantly with advances in technology, especially in the field of deep learning, to the point that it has become embedded in our daily lives: automatic language translation or chatGPT are only some examples.

[svenvanderburg]

I feel like you should mention deep learning here since so much of NLP research and applications are actually deep learning applied to NLP.

[svenvanderburg]

Suggested change

	- Extract vector representations of individual words, visualise it and manipulate it
	- Extract vector representations of individual words, visualise and manipulate them

[svenvanderburg]

Suggested change

- Other?

[svenvanderburg]

Suggested change

	This course covers core concepts of Natural Language Processing (or NLP) and it is designed to equip researchers in the humanities and social sciences with the foundational skills and knowledge needed to carry over text-based research projects.
	This lesson covers core concepts of Natural Language Processing (or NLP) . It will equip you with the foundational skills and knowledge needed to carry over text-based research projects. The lesson is designed specifically with researchers in the humanities and social sciences in mind, but is also applicable to other fields of research.

I think even though you focus on SSH, the lesson will still be useful for others.

[svenvanderburg]

Also, in carpentries lesson material it is common to refer to lesson instead of course

[svenvanderburg]

Suggested change

For the episode 02: Transformers (BERT)

Maybe a minor technical principality: I would suggest to track 'what still need to be added' in issues, so that the lesson is you always a viable product.

[svenvanderburg]

I think this should be part of the setup instructions. Or do you have a good reason for not putting it in there?

[svenvanderburg]

I think the way this part is now, it is a bit like: this gives you an idea of the kind of problems we will tackle, but you can forget everything you just read because we will get back to it anyway. Is that what you intended?

If not you could consider making short subsections and actually naming the problem (word2vec, named entity recognition). And mention the episodes in which you will actually cover this.