Python is a ready-to-use programming language with different packages for loading and playing around with data, visualizing the data, transforming inputs into a numerical matrix, or actual machine learning and assessment.
Most Data Scientists and Machine Learning Engineers prefer using Python for Data Science and developing artificial intelligence and machine learning apps.
Here are 5 Must-have skills in Python for every Data Scientist
If you are a data scientist or want to learn data science with Python track, here are five critical skills you need to develop as a beginner.
And to help you develop these skills, we have linked some of the best available resources to help you become a creative data practitioner.
1. Data Scraping
Gathering data from websites is one of the most logical and easily accessible sources of data.
You need to learn how to turn raw data into actionable insights and once you have a large amount of structured data, you will want to store and process it.
To be an effective data scientist or an engineer, you should be able to wrangle and extract data from relational databases using SQL.
3. Data Frames
SQL is important in data science and great for handling large amounts of data however it lacks Machine Learning and Data Visualization.
So you will have to go through the painful process of enabling Machine Learning services in SQL Server or use MapReduce to get data to a manageable size and then process it using Pandas.
4. Machine Learning
A lot of data science can be done with select, join, and group by (or equivalently, map and reduce) but sometimes you need to do some non-trivial machine-learning.
5. Data Visualization
Data science is about communicating your findings, and data visualization is incredibly valuable part of that.
Before You Go
Data Science is intimidating and exceedingly challenging without mentorship. We hope you will learn all the important skills and also get the personalized guidance you need to land the job you want.
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Wishing you the best with your career!
happy learning . . .