Learning R Programming for Data Science

Explore why data science is the career of the future, as data scientists decode patient records, derive value from the big data deluge, and communicate insights to decision makers.

Understand why data science matters now and why R serves as its backbone. Begin with the basics of R to start your journey as a data scientist.

Explore matrices in R: understand what a matrix is, how to perform matrix calculations, and how to create and access matrix elements by rows or columns using the matrix function.

Explore data frames in R and understand their structure. See mtcars example with mile per gallon, cylinder, displacement, horsepower, and inspect data using head, tail, and str.

Create lists in R with list(), combining vec, mat, and df, and name components to form my_list and shining_list, as shown in ex6_1 and ex6_3.

Explore equality in R by using the double equal sign for comparisons, understand case sensitivity, and compare logicals with numerics through practical exercises on vectors and matrices.

Master relational operators in R, including greater than, less than, and their equal forms, with numeric, string, and logical comparisons. Explore true and false, and practice alphabetical ordering.