The Data Lab teaches two courses the Data Challenge Lab course and the Data Impact Lab course. The Challenge Lab is an introductory course in data gathering, cleanup and analysis. The Impact Lab is where advanced students tackle real world, high impact problems through data analysis.
Data Challenge Lab
Their Data Challenge Lab course is a 10 week course with no pre-requisites that teaches students how to analyze real world data to solve problems.
Their are no lectures. You’re given project datasets and the tools to manipulate, visualize and analyze the data. Your goal is to master the tools, cleanup the data and gather insights from the data. Professors are there to provide one on one help so you can step through the data provided and understand how to use the tools.
In the information provided on their website there were no references and no information about the specific tools used in the Data Challenge Lab to manipulate, visualize and analyze the data. From an outsiders’ viewpoint it would be great to have a list of references or even websites describing the tools being used and maybe the datasets that are accessed.
Data Impact Lab
The Data Impact lab course is an independent study course, whose only pre-req is the Data Challenge Lab.
Here students are joined into interdisplinary teams with practitioner partners to tackle ongoing, real world problems with their new data analysis capabilities.
There is no set time frame for the course and it is a non-credit activity. But here students help to solve real world problems.
Current projects in the Impact lab include:
- The California Poverty Project to create an interactive map of poverty in California to supply geographic guidance to aid agencies helping the poor
- The Zambia Malaria Project to create an interactive map of malarial infestation to help NGOs and other agencies target remediation activity.
Previous Impact Lab projects include: the Poverty Alleviation Project to provide a multi-dimensional index of poverty status for areas in Kenya so that NGOs can use these maps to target randomized experiments in poverty eradication and the Data Journalism Project to bring data analysis tools to breaking stories and other journalistic endeavors.
Courses like these should be much more widely available. It’s almost the analog to the scientific method, only for the 21st century.
Science has gotten to a point, these days, where data analysis is a core discipline that everyone should know how to do. Maybe it doesn’t have to involve Hadoop but rudimentary data analysis, manipulation, and visualization needs to be in everyone’s tool box.
Data 101 anyone?
Photo Credit(s): Big_Data_Prob | KamiPhuc;