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This class is a comprehensive introduction to data analysis with the Python programming language. This class targets people who have some basic knowledge of programming and want to take it to the next level. It introduces how to work with different data structures in Python and covers the most popular data analytics and visualization modules, including numpy, scipy, pandas, matplotlib, and seaborn. We use Ipython notebook to demonstrate the results of codes and change codes interactively throughout the class.
This course is a 35-hour program designed to provide a comprehensive introduction to R. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which you will learn the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.
Practical skills for visualizing, transforming, and modeling data in R. During this two-day course, you will learn how to explore and understand data as well as how to do basic programming in R.Who should take this course? This class will be a good fit for you if you are just starting with R or have dabbled in R, but wish to improve your skills. No…
This course is a 2-day intensive workshop on basic R programming. You’ll learn how to load, save, and transform data as well as write functions, generate graphs, and run basic statistical models. You’ll acquire not only the theoretical framework that helps you understand the process of data analysis, but also practical skills that allow you to utilize as soon as you get back from the course.