In this module, you will embark on an exciting journey of learning as you explore data visualization using Pandas, Seaborn and Matplotlib. You will use Pandas and Seaborn to construct histograms, which will allow you to gain insights into the distribution of your numerical data. You will also delve into scatterplots, enabling you to visualize the relationships between different variables in your datasets and identify patterns and correlations. Lastly, you will learn how to utilize line plots to capture temporal trends and changes over time, enhancing your ability to communicate data-driven narratives effectively.

In this module, you will explore the powerful combination of Plotly, Dash, and Streamlit for creating interactive and dynamic visualizations within a dashboard. You will use Plotly to create visually appealing histograms, scatterplots, and line plots that can be embedded within a dashboard. You will also dive into Dash and Streamlit, two popular Python frameworks for building interactive web-based dashboards. By the end of the week, you will be able to apply your knowledge and create a comprehensive dashboard that incorporates these visualizations, enabling users to explore and interact with your data.

In this module, you will dive into two cloud-based tools, Tableau and Amazon QuickSight, to create compelling visualizations, and gain insights from your data in a user-friendly and interactive manner. You will first use Tableau to design and create histograms, scatterplots, and line plots that effectively showcase your data. You will then use Amazon QuickSight, an intuitive and cloud-based business intelligence tool, to create visually appealing and interactive visualizations. By the end of the week, you will be able to apply your knowledge and create captivating visualizations using these platforms.