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Updated in [July 27th, 2023]
This course is designed to help new learners become familiar with Jupyter Notebook and its features to perform various data science tasks in Python. Through the course, participants will start from basic data analysis tasks in Jupyter Notebook and work their way up to learn some common scientific Python tools such as pandas, matplotlib, and plotly. Real datasets, such as crime and traffic accidents in New York City, will be used to explore common issues such as data scraping and cleaning. Insightful visualizations, showing time-stamped and spatial data, will be created. By the end of the course, participants will feel confident about approaching a new dataset, cleaning it up, exploring it, and analyzing it in Jupyter Notebook to extract useful information in the form of interactive reports and information-dense data visualizations. The course is taught by Dražen Lucanin, a developer, data analyst, and the founder of Punk Rock Dev, an indie web development studio.
Course Syllabus
Jupyter Notebook Introduction
Data Analysis Using Pandas
Scraping Data
Advanced Visualization
Analyzing Geographic Data