Chapter 3 What should I learn?
Modern scientific coders often operate with many coding languages and software in our workflows. But getting started, we often have a primary language that we use along with a suite of concepts and that help us develop workflows and interoperate between languages and software to do our analytical research. Learning one language to do a task at hand can help you develop skills and mindsets that can be transferable when you come upon other tasks.
A great thing about modern computation is that there are multiple ways to do the same thing. But this can also be a really challenging thing too: what should you learn? And in which order? This chapter aims to help you find resources to learn what you need.
3.1 Learn a new language
Introductory tutorials will help you install software and get comfortable using it. They will also and help you develop the mindset to seek out existing code that works (including your own!) and adapt it for your analyses.
You want to learn:
3.2 Image analysis
Learn more about image analysis techniques and software with the image.sc community…11.3
You want to learn:
- CellProfiler… https://cellprofiler.org/
- ImageJ…
- QuPath… https://qupath.github.io/
- Napari… https://github.com/sofroniewn/napari-training-course - Nick Sofroniew
3.3 RNA Sequencing
- Molly Hammell software
- Gene Yeo UCSD course
3.4 Project Management & Workflows
3.6 Data Sharing
Platforms for data sharing
3.7 Machine Learning (ML)
- Intro to ML conceptually …
- Intro ML in R….4.7
- Intro ML in Python….
3.8 Plotting
should this be a section or page?
3.10 Containers
- Docker …