Master the basics of data analysis by manipulating common data structures such as vectors, matrices and data frames.
Master the basics of data analysis in Python. Expand your data science skill set by learning scientific computing with numpy.
Continue your journey to become an R ninja by learning about conditional statements, loops, and vector functions.
Learn how to parse data in any format. Whether it's flat files, statistics software, databases, or web data, you'll handle it all.
Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.
In this course, you'll learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames.
Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.
Learn the fundamentals of writing functions in R so you can make your code more readable and automate repetitive tasks.
Strengthen your knowledge of the topics you learned in Intermediate R with a ton of new and fun exercises.
Learn to explore your data so you can properly clean and prepare it data for analysis.