Author: Mohamed NIANG, ML Scientist

This repository contains notebooks on introduction to data science with Python. In this course, we will discuss the Python libraries particularly used in Data Science: Numpy, Pandas and Matplotlib. We will successively review Numpy objects and Pandas objects to analyze real-world data. We will also learn how to choose the right type of graph to visualize the desired data. We will have the opportunity to apply the practice through several datasets.

1. The numpy library in Python
2. Data analysis with numpy in Python
3. The pandas library in Python
4. Data manipulation in pandas with Python
5. Handling missing values in Python
6. Data analysis in Python
7. Pandas series in Python
8. Pandas dataframes in Python
9. Intermediate data analysis in Python
10. Matplotlib in Python
11. Bar and scatter plots in Python
12. Histograms and boxplots in Python