In this course, you'll learn how to gather, manipulate, and analyze real-world data through hands-on projects. Starting with the Python libraries NumPy and Pandas, you'll then move into exploring various plotting solutions with a focus on data visualization. Alongside traditional tools like Matplotlib and Seaborn, you'll also learn to use Plotly and Dash Enterprise, both powerful options for creating dynamic dashboards.
As you progress, you'll gain valuable experience working on real-life projects that can be deployed online using Heroku and GitHub. Your analytical projects on GitHub will showcase your data science skills and demonstrate your approach to coding and analysis, which can prove crucial when seeking future employment. Each lesson is split into two parts: first you'll learn new concepts, then you'll apply them to a project of your choice, whether it ties into your professional field or another area of interest. The instructor will guide you in selecting a suitable dataset, walk through best practices, and help with coding as needed.
What You Will Learn
- Plan and present a data story
- Gather and manipulate data from different sources
- Uncover data stories through exploratory data analysis
- Manipulate data with the NumPy and pandas libraries
- Use advanced Python visualization libraries like Plotly and Dash
- Build a dashboard
- Apply the rules of effective dashboard design to create professional data science solutions
- Go live with your project and deploy the dashboard on a live server
This course is available for 30 days. You can choose when to start your access period. Once you activate, you will have 30 days to complete it (access the course materials, quizzes, projects and videos). You may request one extension of seven (7) days. Other extension requests will be evaluated on a case-by-case basis. Videos are not downloadable.
