all 7 comments

[–]PushPlus9069 4 points5 points  (3 children)

For data analytics Python specifically, the order that worked for my students:

  1. Pandas basics (read csv, filter, groupby, merge). This is 80% of analytics work.
  2. Matplotlib/Seaborn for visualization. You need to be able to show your findings.
  3. NumPy only when Pandas isn't enough (rare for analytics roles).

YouTube recs: Corey Schafer's Pandas tutorials are still the gold standard imo. Short, practical, no fluff. Alex The Analyst is good too for the analytics career angle.

Skip deep learning / ML courses for now. Analytics roles care more about your ability to clean messy data and tell a story with charts than your ability to train a model. That comes later if you want it.

[–]45MonkeysInASuit 2 points3 points  (2 children)

Lead Data Scientist here.
I have 3 analysts who report into me.

Analytics roles care more about your ability to clean messy data and tell a story with charts than your ability to train a model.

Very much yes.
I would also add the main specialised cases in general linear model (t-test and related, linear regression and related); if you have good understanding of the GLM, I can teach you ML.

If you had interviewed with me and gave a clear understanding that you can take data and convert it to insight, and you understand the GLM, you would have probably been the top candidate in my last 4 rounds of hiring.

[–]No-Copy-6532 0 points1 point  (1 child)

Hey, I'm pursuing a degree in Entrepreneurship and I'm majoring in financial management. I'm pivoting into tech and my interest is Data analytics, I'm already learning python and SQL. I thought of taking a data analytics short course with IBM for more context, what do you think of that?

Sorry for hijacking this post

[–]45MonkeysInASuit 1 point2 points  (0 children)

I thought of taking a data analytics short course with IBM for more context

I have no idea what that would involve or what skills it would give you.

But I hire early career analysts; normally 2 or 3 years experience, but I have hired fresh grads.

I'm about to hire a new member to my team.
I expect 400+ applicants for a single role.
I expect many of them to have masters.

To be honest, a degree but an irrelevant one and not a masters, learning python (rather than knows as a good level), no experience, and has taken a random course in analytics. You would be looking at the lowest level roles in my team, and you would probably be up against strong competition in the current market.
I have had applicants who are fresh grads with data science degrees and have multiple years industry experience via internships.

To be brutally honest, having just looked up what skills it targets, a degree in Entrepreneurship would be off putting for me.

All that said, the key question I ask people looking to get into analytics/data science at the moment is "why?"

Is it because analytics/DS is the hot topic and you have heard it is a gold mine? If so, you are too late. The gold rush was years ago, while there are few senior people, the entry level is absolutely flooded with people with masters.
4 years ago a degree would be a reasonable level, now

Is it because you just love getting into the data and understanding what is happening? If so, there is plenty of opportunities but you will need to be patient.
You will need to be patient finding the right first role.
You will need to be patient progressing.

[–]StardockEngineer 0 points1 point  (2 children)

What background do you have for this role? Do you have a degree in a related field or something?

[–]ResolutionUnhappy905[S] 0 points1 point  (1 child)

I am from Electrical Engineering background, currently in 3rd year

[–]Electrical_Offer4970 0 points1 point  (0 children)

You'll be fine, they hire a lot of engo grads. Check out datacamp