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Tools for Data Analysis introduces elements of programming and statistical methods for data analysis and data science. You will learn how to use the R and Python programming languages—the most popular and in demand languages for data science—as well as shell scripting, to interact with data (visualization, manipulation), automate tasks (web scraping, file management) and deploy machine learning methods. The course is hands-on: students get to work on mini-projects and practical exercises throughout the lectures; theory of the methods is touched upon and references for self-study are provided. The course is aimed at students willing to acquire programming skills to work with data. Ideally, they have already taken statistics courses. People without such a background can still attend, but will require additional effort to assimilate the theory. Experienced analysts can still benefit from the course, by using it to transition to Python or R, or for a systematic review of
common techniques.
common techniques.
This course is part of the “Labor, Development & Policy evaluation” Program. If you wish to follow this course, you need to enrol via the Program at this link.
