In order to be useful within a professional environment, data must be structured in a way that can be understood and applied to real-world scenarios. This course introduces using Python to perform statistical data analysis and create visualizations that uncover patterns in your data. Using the tools and workflows you developed in earlier courses, you will carry out analyses on real-world datasets to become familiar with recognizing and utilizing patterns. Finally, you will form and test hypotheses about your data which will become the foundation upon which data-driven decision-making is built.
It is recommended to only take this course if you have completed Constructing Expressions in Python, Writing Custom Python Functions, Classes, and Workflows, Developing Data Science Applications, Creating Data Arrays and Tables in Python, and Organizing Data with Python or have equivalent experience.
Faculty AuthorChris Myers
Benefits to the Learner
- Carry out analyses on a real-world dataset
- Perform statistical data analysis and visualization
- Use grouping operations to further data analysis
- Use Python to explore your own dataset
- Data analysts and business analysts
- Database managers
- Technical and systems analysts
- Programmers interested in data science
- Business managers
Applies Towards the Following Certificates
- Python for Data Science : Core Courses