The tools you use, and the way you approach learning can have a significant correlation with how much you get paid for your work as a data scientist.
- Python 3
- Pandas
- NumPy
- Matplotlib 3
- Seaborn
This project explores the differences between the tools used by the highest-paid 20% of data scientists and the bottom 50% lowest-paid. As well as the differences in how they approach learning. Read the article here >>
Untitled.ipynb - This notebook contains the code used for the entire exploratory analysis process and the explanatory visualizations.
datasets - This file contains the data sets from the 2021 Kaggle and Stack Overflow surveys.
- kaggle-survey-2021
- stackover_anudevsurv_2021
Among the most interesting findings regarding the differences between lower-paid and higher-paid data scientists where the use of Gradient Boosting Machines, SQL, and the Cloud Platform they have worked with
I would like to thank all Udacians for motivating me and guiding my data science journey.