R Programming A-Z™
R For Data Science With Real Exercises!

Supplement what you're learning in class with this course. I also just started learning R this semester and this dude teaches it better than my prof. https://www.udemy.com/course/r-programming/

Udemy is good for those on a low budget and most good teachers there do respond to student questions.

In terms of R courses there, this course with 4.6 stars from 36.6k ratings seems well presented. Or this one with 4.6 stars from 12.1k ratings.

Når du er færdig med at lære Python som mange andre har anbefalet, og som også er et rigtigt godt sted at starte, vil jeg anbefale at du kigger på programmeringssproget R.

R-programmering er meget anderledes end Python, i den forstand at man mere bruger det som et værktøj til at arbejde med data, end til at lave komplette programmer.
Det bruges utroligt meget i den finansielle verden til at arbejde med datasæt og statistik, generere smukke diagrammer, osv.

R er noget mere kompliceret end Python, da der ikke er specielt meget dokumentation til R. Til gengæld er der folk der får jobs udelukkende på at kunne R, fordi store virksomheder ved at det er et kraftfuldt værktøj til statistik og sandsynlighedsberegninger. Jeg vil varmt anbefale to kurser lavet af en gut på Udemy ved navn Kirill Eremenko: Basic, og Advanced. Det er en af de få kilder jeg har fundet, der ikke kræver at man står på hovedet i dokumentationen for selv at finde svar på hvordan ting virker.

Without knowing your background, I would start following Matt Dancho on linkedin. There's a number of routes you can take. I would opt with the Udemy first to get your feet wet. It's a cheaper route.

https://www.udemy.com/course/r-programming/

There's a number of financial risk courses with R. Here's just one. Generally anything above a 4.5 rating in udemy or coursera is half decent.

https://www.coursera.org/learn/financial-risk-management-with-r

https://www.udemy.com/course/r-programming/

https://www.udemy.com/course/data-science-and-machine-learning-bootcamp-with-r/

Don't wait for the axe to fall. Start learning today!

Few free data science courses on Udemy for 3 days (Offer ending today)

1. Data Science A-Z™: Real-Life Data Science Exercises Included
2. R Programming A-Z™: R For Data Science With Real Exercises!
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4. Tableau 10 A-Z: Hands-On Tableau Training For Data Science!
5. Power BI A-Z: Hands-On Power BI Training For Data Science!
6. Python for Statistical Analysis
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It's definitely great that you are taking the initiative early. Bioinformatics really involves the use of data science and machine learning tools to analyse biological data. Therefore, a lot of the tools and analyses you use in bioinformatics will also be relevant for other fields, such as business, marketing, etc. If you want to get into bioinformatics, here is what I recommend:

1. Learn a coding language for data science: The two main coding languages here are R and python. Python is great for data science and general programming whereas R is mainly focused on data science. I personally learnt python as an intro to programming. However, I am currently using R for data analysis as it is vastly superior in terms of simplicity of data visualisation and statistical analysis. If you want to learn python, This is a great online course https://www.udemy.com/course/complete-python-bootcamp/. Alternatively, if you want to learn R, this online course is also a great starting point https://www.udemy.com/course/r-programming/. If you want to dive deeper into R, then I would recommend this textbook https://r4ds.had.co.nz/. This is like the golden manual of R.
2. Learn the basics of machine learning: For that, I would recommend this textbook https://trevorhastie.github.io/ISLR/. This book introduces the major machine learning/statistical learning techniques used in data science and guides you through their implementation in R. It's definitely a good read, and it's quite simple. The fact that the book uses R definitely helps because it allows you to apply what you learnt from point 1 to real-life data sets.
3. Learn BASH scripting (Optional): BASH is the bourne-again shell, and it is the command line interpreter for linux. A lot of bioinformatics tools are best optimised for linux (I think), and that's why it's a good idea to learn how to use Linux commands and understand simple scripts. There are a lot of resources online. I am currently using some linkedin learning courses, but I doubt your school has access to that. You can definitely find a lot of good resources online though.

This is all the advice I have. My number 1 tip would be to learn a coding language (R preferably if you have your mind set on data analysis or python if you want a fun intro to programming).

I am very new to the field myself, and I am doing a lot of catching up right now (my background is completely biology). However, it is definitely an exciting field.

Several highly rated DS, ML, Python, Tableau, PowerBI video learning courses are free to purchase (only for 1 day), buy them before they are gone tomorrow. pass these to others who may be interested.

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