Find what you already know, what you need, and the next steps
Here’s a quick summary of what you should read:
Already Have The Skills: Read the Getting Hired, don’t need the others.
Completely New: Start by reading the Data Analyst Section. You need to get your foot into a Data Analyst Role ASAP.
Level Up From a Data Analyst: Just read the For MLE/Data Scientists section
If you have the skillset already, read the posts below.
These posts should answer 90% of your hiring related questions.
For Data Analysts
If you are completely new to the field, and have not acquired R/Python, this is your starting platform
Congrats, even if things don’t work out, you are now qualified for a simple dev job using Python/R
Structured Query Language
Aah, good old SQL, the lifeblood of all data professionals. You’ll be heavily grilled for your SQL knowledge. Be prepared
Don’t know Linear Algebra
If you already know how to code, but don’t know any linear algebra, then start here:
At this point, you should be able to read basic data wrangling techniques confidently and with reasonably proficiency
Don’t know Statistics
You have now acquired basic programming, and lin alg, and are ready to progress to basic statistics here:
At this point, you should be able to read most research papers without too much trouble
Linear Regression (Linear Modelling)
At this point, you can start to learn about your first modelling technique called Linear Regression, start here:
Having completed the first two posts, If you understand what’s going on in the first 2 posts, and understand some basic SQL queries, you now have the skill set for extremely basic data analytics jobs.
If you have already had some exposure to regression analysis, here are some algorithms examples you can look at that deal with classification problems:
Logistic Regression - this is classification, don’t let the title fool you.
Here are some statistical biases you will see in your dataset, and in what domain you will encounter them in. Additionally, a quick solution as to how to keep your analysis clean, or remove the bias is in the article as well.
Look-ahead Bias - a bias related to time series analysis.
Backfill Bias - a bias everyone analyzing stocks and portfolios will encounter.
Allocation Bias - for those that work in the medical industry.
Verification Bias - for those working with customer data
For MLEs/Data Scientists
Only read this section here, if you’ve already got some relevant data work experience. A certificate, or an online course doesn’t count. We only value your work experience if it was done in the real world.