Certificate in Data Science with R

Data Science with R

About Data Science with R

To manage, store, and analyze data in data science, R is utilized. It may be applied to statistical modeling and data analysis. R is a statistical analysis environment. R contains a number of statistical and graphical features.

Why is Data Science with R important?

R is the perfect tool for manipulating data. It permits the use of a number of preprocessed packages, greatly simplifying data wrangling. One of the key reasons R is favored in the data science field is because of this. The ggplot2 package, which R offers, is well known for its visualizations.

Who should take the Data Science with R Exam?

• Data Scientists
• Machine Learning Engineers
• R Programmers
• Data Analysts & Advanced Data Analytics Professionals
• Software Engineers
• Developers
• Chief Technology Officers (CTOs)
• Statisticians and Data Science Researchers
• Data Engineers
• R Programmers Analytics
• Python programmer
• Data Science Engineers

Data Science with R Certification Course Outline

1. Overview of Data Science with R
2. Learning Path for Data Science
3. Data Collection and management
4. Model deployment
5. Loading data into R
6. Data Science and Machine Learning
7. Cleaning of data
8. R Cross-validation
9. Data Transformation
10. Linear Regression
11. Clustering
12. K-means algorithm
13. Unsupervised Methods
    
14. Decision tree