Become an expert in the various data analytics techniques using R. Master the data exploration, data visualization, predictive analytics, and descriptive analytics techniques. Get hands-on practice on R CloudLabs by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music Industry, and on unemployment. The course is best suited for beginners as well as experienced professionals who want to use R for data analytics.
Data Science Certification Training – R Programming
The Data Science with R training course has been designed to impart an in-depth knowledge of the various data analytics techniques which can be performed using R. The course is packed with real-life projects, case studies, and includes R CloudLabs for practice.
Mastering R language: The course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R.
Mastering advanced statistical concepts: The course also includes the various statistical concepts like linear and logistic regression, cluster analysis, and forecasting. You will also learn hypothesis testing.
As a part of the course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and Internet. R CloudLab has been provided to ensure a practical and hands-on experience. Additionally, we have four more projects for further practice.
- Gain a foundational understanding of business analytics
- Install R, R-studio, and workspace setup. You will also learn about the various R packages
- Master the R programming and understand how various statements are executed in R
- Gain an in-depth understanding of data structure used in R and learn to import/export data in R
- Define, understand and use the various apply functions and DPLYP functions
- Understand and use the various graphics in R for data visualization
- Gain a basic understanding of the various statistical concepts
- Understand and use hypothesis testing method to drive business decisions
- Understand and use linear, non-linear regression models, and classification techniques for data analysis
- Learn and use the various association rules and Apriori algorithm
- Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering