Hi all, crowdsourcing a bit of advice on how best to proceed…
I’m working through the Data Analyst pathway and I’ve completed the Introduction to Python (Fundamentals & Intermediate). After completing Fundamentals, I jumped into Practice Mode and worked through the practice problems – some of it was quite tough and I spent a lot of time on Stack Overflow, but I got there in the end.
Same process for Intermediate – I worked through the course and guided project and then went into Practice Mode to work on the relevant problems (as well as the ones for Lists, Dictionaries and Sets). However, I’m getting pretty badly stuck on a number of these, even to the extent that sometimes I review the solution and still don’t have a good grasp of it – for me, it’s a reasonable jump in difficulty from the main courses.
I’m trying to determine my best option – should I forge ahead into Intermediate Python and Pandas and aim to complete the Data Analyst pathway and circle back to Python fundamentals and practice problems at a later date? Or do I put the Dataquest path on pause and keep working on Python fundamentals elsewhere…HackerEarth, freeCodeCamp, etc.?
Genuinely not entirely sure if it’s best to blast through the pathway and then work to improve my competencies or take it a bit slower with Python (which would entail doing more learning and practicing elsewhere).
Thanks for reading!
Personally, I feel that if you can go through the course content without a problem, then that’s a pretty good indication for ‘go-ahead’.
I just finished the Data Scientist path myself this week, and I only did the first two practices. The ability to write Python code really hasn’t been a problem. To add a little context, I wasn’t a programmer before, I learned Python fundamentals in a Udemy Data Science course for a couple of weeks before starting here. (I ditched that course because the teaching style was bugging me so much…) Actually, I even skipped the Python part since I just did the fundamentals on Udemy and the highly similar content just wasn’t interesting enough for me to focus on at the time. I did go back and finish the Python part near the end of the path.
I guess my point is, you don’t need to be Python invincible to continue the path. And you will definitely get to learn & practice more along the way.
That being said since I haven’t done much practice in practice mode, I’m not sure if getting through the practice questions is essential, but I doubt it is. I would recommend at least give yourself a timeframe or taking a few more modules to feel it out.
Hope this helps!
That does indeed help, I appreciate you taking the time to share your perspective with me!
I’m coming from a similar place in that I’m new to programming and thinking it over after reading your reply, I think I’m likely putting a lot of pressure on myself to become ‘Python invicible’ quite quickly.
I’ll likely be better off setting myself the tangible goal of completing the full Data Analyst path and then circling back to the practice problems and improving my competencies from there. I think I’m getting a bit sidetracked with considering how to improve my skills with the Python fundamentals and it’s lowering my productivity (as I’m not just focusing on the core modules).
I think I’ll try to revise some of what I’ve already covered, finish off the full path and then revisit my weaknesses. Thanks again!
@colleen.mccaskell Glad to be of help.
I feel the same about putting pressure on myself to be ‘invincible’ at something I’m learning too, especially with Data Science. Even realizing that it’s kind of a trap – considering the never-ending things to learn, and what counts as being ‘invincible’ anyway? – my mind just goes there. Imposter syndrome isn’t an uncommon thing, but I think the importance is to be aware of it and just keep learning and keep yourself occupied.
What I find helpful in particular is to try and help others in the community. You learn along the way trying to solve what Douglas Adams called a ‘SEP’ – somebody else’s problem and most importantly you get validation of your competency.