Using Jupyter and Python for Data Analysis
This course will build on your knowledge of Python to sharpen your skills for data manipulation and analysis. We will use libraries such as pandas, numpy and matplotlib to ingest, tidy and explore real world datasets and extract insights from them. We will leverage the Jupyter notebook interface to help us work with public APIs, combine multiple datasets and perform exploratory analysis. At the end of the course you should feel comfortable working with unfamiliar datasets, spotting common data errors and using visualizations to understand your data and plan more detailed analysis.
In this session we will review some basic programming problems and solve them using python
In this session we will build on the content of the python/jupyter course as well as the first problem session and explore some more complex problems which include external data sources.