GETTING STARTED WITH R TRAINING :
The Getting Started with R training is designed for both the developers and data scientists. This training will give the attendees a good understanding R language, data exploration and use of machine learning models using R. The training is designed to provide good hands-on experience for all the topics. During the training participants will develop a predictive model using real data. The training is effective for a class size of 10-15 participants.
After the course
Once the course is complete, you will be able to achieve the following:
- Understand programming constructs and data types in R.
- Import different data formats and export results
- Use R for data exploration and basic descriptive analytics.
- Apply machine learning models like regressions on the data.
The participants should have the basic knowledge of Windows system as the training may require them to do some basic operations. Participants should also have basic understanding of statistics terminology like mean, standard deviation, correlation etc. Working knowledge in similar tools/packages like Weka, SAS etc. would be an added advantage.
You may also need to bring a Windows Laptop, minimum with the following configuration:
- At least 2 GB RAM on the laptop.
- At least 10 GB of space on Hard Drive.
- 1.4 GHz CPU or above.
- DVD drive
- USB port
- MySql 5.x (Optional)
Schedule of R Training:
Introduction to R
Covers historical background and origin of R platform, packages. It also covers how to install R and packages; and get help
R Language – Data
Describes basic data type, vectors, arrays, metrics and data frames, how to input data, print data and imputations
R Language – Import/Export data
Participants would learn different format types supported for importing large amount of data; how to import and export data.
R Language – Programming Constructs
Introduces programming language syntax and constructs to write control statements, loops and functions.
R Language – Text handling
Students will learn how to use textual data in R and will introduced regular expression features and utilities like regexp, grep etc.
This session will introduce data exploration capabilities of R. Participants would be able to explore data, generate basic statistics and view the results.
Participants would learn how to visualize the data and results and export the visualizations
Participants would develop simple programs to handle the data and perform descriptive analytics.
In this session, students would be exposed to modeling algorithms in R. Focus will be regressive models and clustering.
Predictive Analytics Project
In this project students would take data from real-life environment and use R to explore the data and build predictive model.