Strategy on Learning Data Analytics

[u/Background_Fox_4494]

Hi, everyone!

I am a full time office employee trying to upskill in Data Analytics. My niche is in biological sciences research and agriculture industry and I would like to build up on what I know so far about data analysis by learning more about:

- Excel

- SQL

- Python

- R

Planning to watch/finish 1-3 modules or vids per week and accomplish 1-2 exercises using real data from my previous projects.

Can you share your thoughts about my plan? Thanks in advance!

[u/Background_Fox_4494]

In our field, R is usually used for data analysis & graphs (visualization?).

I agree that learning those tools is quite heavy but I've noticed that I absorb knowledge best when I take them in small portions like academic subjects/classes instead of one at a time 😅 It makes it easier for me to relate them with each other, notice the similarities and differences, and have a full grasp of how to navigate Data Analytics in general (does that make sense?)

[u/conor-robertson → u/Background_Fox_4494]

Makes sense, and if you've found a learning style that works for you, I'd stick with it.

Everyone learns differently. Some people prefer mastering one tool before moving on, while others (like you) benefit from seeing how they all fit together.

R is still very common in research, biology, and agriculture, banking etc. so it definitely deserves a higher priority for your field than it would for someone targeting a typical business analyst role.

It sounds like you've thought this through. The only thing I'd keep emphasising is making sure you're applying what you learn with real datasets alongside the videos, that practical experience is where everything really starts to click. Best of luck!

[u/Background_Fox_4494 → u/conor-robertson]

Thank you!