Are you fresh out of a bootcamp? Then in my opinion, these are a few things you need to learn and apply, to score the data science career you are looking for.
1) How to deal with missing data?
Missing data are very common in the industry, thus it is important for data scientist to know who to handle missing data, given that there are myriad ways to handle missing data, from replacing with mean, or realising there is no need to fill up the missing value all the way to using linear/logistic regression. Learn them, it will be useful!
2) Analysing data
NO! Data scientist have to learn how to analyse data, because they need to ascertain the quality of the data before feeding it into a machine learning model. Rubbish In, Rubbish Out. Data Scientist have to ascertain the quality of data and this is where analysis skills comes in.
Moreover, through analysis it helps the data scientist to better understand the biz process and collection process of data.
3) Structuring Dataset
In most of the boot camps, given the time constraint, the dataset are usually prepared in advance. But in the industry, you get denormalized data which you will need to build up to the dataset that you need for your analysis or machine learning. This is something you will need a lot of practice on. Start practicing!
Congrats on completing your boot camp/course but the learning journey continues. I hope the above learning suggestions will put you in a direction to your dream data job. :)
I wish you all the best in your data learning journey! :)
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