Data Analysis
Python for Data Science: Fundamentals Part I Course
This is my Dataquest course code covering topics such as Variables and Data Types, Lists and For Loops, and Conditional Statements.
Python for Data Science: Fundamentals Part II Course
This is my Dataquest course code that includes the topics Dictionaries and Frequency Tables.
Source
Python for Data Science: Intermediate Course
This is my Dataquest course code covering topics such as Cleaning and Preparing Data, Object-Oriented Programming, Data Analysis Basics, and Working with Dates and Times in Python.
Python Basics for Data Analysis Path
I completed the courses in the Dataquest learning path for Python Basics for Data Analysis.
Utilizing a data set on a bike-sharing program in Boston, Massachusetts, I created different visualizations based on weekend/weekday usage, the peak time of usage, and more.
As part of a 12-hour workshop on data visualization and storytelling, I learned about the fundamentals of data visualization, which can be used to support data-driven decision-making. I learned about design principles used in creating effective visualizations and how to create a narrative that supports the data, provides context, and reveals actionable insights.