Learn all about R Programming and how to use it for data analytics.
Section 1: Introduction to Basics - Take your first steps with R. Discover the basic data types in R and assign your first variable.
Section 2: Vectors - Analyze gambling behavior using vectors. Create, name and select elements from vectors.
Section 3: Matrices - Learn how to work with matrices in R. Do basic computations with them and demonstrate your knowledge by analyzing the Star Wars box office figures.
Section 4: Factors - R stores categorical data in factors. Learn how to create, subset and compare categorical data.
Section 5: Data Frames - When working R, you’ll probably deal with Data Frames all the time. Therefore, you need to know how to create one, select the most interesting parts of it, and order them.
Section 6: Lists - Lists allow you to store components of different types. Learn you how to deal with lists.
Section 7: R Graphics - Discover R’s packages to do graphics and create your own data visualizations.
Section 8: R built-in functions and R packages.
Section 9: Machine Learning using R (Naïve Bayes, Recommender, K-means, Time Series).
Section 10: Various case studies using R.
Section 11: R on Hadoop/Spark.
Big data and cloud consultant. Trained 100+ students from US/Canada/Australia. Associated closely with IIT and IIM alumni for sharpening knowledge on demand. Corporate training delivered to the clients for the last 6.5 years.