Before you start practicing R programming, you should thoroughly understand the basic concepts of R programming, such as operators, variables, data types, functions, and graphs, by implementing them in a simple dataset. Then, you should work on data exploration, manipulation, and visualization by picking up a use case, along with a dataset.
Finally, as R programming is also used to build Machine Learning models, you should acquire a thorough knowledge of Machine Learning algorithms as well. For this, you can move on to a larger dataset online, which includes a problem statement, and implement all the algorithms to check the one that works the best for the scenario. This is the best way to practice R programming and get a thorough understanding of all the concepts.