"A picture is worth a thousand words". Everyone is familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.

One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions.

The main goal of this Data Visualization with Python course is to teach learners how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, learners will be using several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium.

Learning outcomes are:

1. describing the importance of data visualization;
2. relating the history of Matplotlib and its architecture;
3. applying Matplotlib to create plots using Jupyter notebooks;
4. discovering how to read CSV files into a Pandas DataFrame; process and manipulate the data in the DataFrame; and generate line plots using Matplotlib.

Learners will gain skills in Python Programming, Data Virtualization, Plotly Matplotlib, Data Visualization (DataViz).