Our Courses
R Programming
Terms & Conditions
Charges for the Training is NON REFUNDABLE, NON TRANSFERABLE, NON-EXTENDABLE.
Timings & Dates may vary.
In case of cancellation of Training from our side, the participants of the cancelled Training will be given an option to be upgraded to another Training. If the offer is denied by them, only then will they be considered for a refund.
If In Any Case training is cancelled by Organizers due to any reason, we will refund the fee after deducting Bank Changes.
If you are not satisfied with our teaching,then drop us email at info@smartcodingg.com
Refund will be in 3 stages:
Verification>>Approval>>Bank Credit through the same mode of payment.
Cash refund is NOT possible under any circumstance.
We are not responsible for any software failing to run/install on the participant's laptop owing to different configurations in laptops.
If you are not satisfied with the quality of services provided during the Training, drop us a mail @ info@alvinitsolutions.in
- Live classes will be conduct from Monday-Friday. You Will Also Get Life Time Access of Recorded Sessions.
- Code files will be provided.
- 2+ Live Projects
- Query solving sessions
- Certification of Completion
What you will take after course?
R Programming Syllabus
R is a well-developed, simple and effective programming language which includes conditionals, loops, user defined recursive functions and input and output facilities. R has an effective data handling and storage facility, R provides a suite of operators for calculations on arrays, lists, vectors and matrices.
Syllabus Of R Programming
Introduction to R Programming
Business Analytics
Analytics concepts
The importance of R in analytics
R Language community and eco-system
Usage of R in industry
Installing R and other packages
Perform basic R operations using command line
Usage of IDE R Studio and various GUI
R Programming Concepts
The datatypes in R and its uses
Built-in functions in R
Subsetting methods
Summarize data using functions
Use of functions like head(), tail(), for inspecting data
Use-cases for problem solving using R
Data Manipulation in R
Various phases of Data Cleaning
Functions used in Inspection
Data Cleaning Techniques
Uses of functions involved
Use-cases for Data Cleaning using R
Data Import Techniques in R
Import data from spreadsheets and text files into R
Importing data from statistical formats
Packages installation for database import
Connecting to RDBMS from R using ODBC and basic SQL queries in R
Web Scraping
Other concepts on Data Import Techniques
Exploratory Data Analysis (EDA) using R
What is EDA?
Why do we need EDA?
Goals of EDA
Types of EDA
Implementing of EDA
Boxplots, cor() in R
EDA functions
Multiple packages in R for data analysis
Some fancy plots
Use-cases for EDA using R
Data Visualization in R
Story telling with Data
Principle tenets
Elements of Data Visualization
Infographics vs Data Visualization
Data Visualization & Graphical functions in R
Plotting Graphs
Customizing Graphical Parameters to improvise the plots
Various GUIs
Spatial Analysis
Other Visualization concepts