Data Visualization with Python (Coursera)

Throughout the course, a consistent dataset will be used for exercises, enabling you to focus on mastering the visualization tools rather than getting caught up in the intricacies of the data. The emphasis is on practical application, allowing you to learn and practice the tools in a real-world context. To fully leverage the Python sections of this course, prior experience programming in Python is recommended. Additionally, a solid understanding of high-school level math is expected. Familiarity with the Pandas library will also be beneficial.
By the end of this course, you will possess the necessary skills to become a proficient data storyteller and visual communicator. With the ability to create compelling visualizations and leverage the appropriate tools, you will be well-equipped to navigate the world of data and make informed decisions that drive meaningful impact.

What you'll learn

• Apply Python, spreadsheets, and BI tooling proficiently to create visually compelling and interactive data visualizations.
• Formulate and communicate data-driven insights and narratives through impactful visualizations and data storytelling.
• Assess and select the most suitable visualization tools and techniques to address organizational data needs and objectives.

Syllabus

Data Visualization Fundamentals
Module 1
This week, we will introduce you to the fundamentals of data visualization and provide step-by-step guidance on how to get started with creating basic plots in Excel and Google Sheets. Whether you are new to data visualization or looking to enhance your skills, this week will lay the groundwork for effective visual storytelling using these widely accessible tools.

Pandas, Seaborn and Matplotlib
Module 2
This week, 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.

Plotly, Dash and Streamlit
Module 3
This week, 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.

Visualization with Cloud-Based Tools: Tableau and Amazon Quicksight
Module 4
This week, 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.