Course Overview – R Analytics
R is a popular programming language and software environment for graphics and statistical computing. It is widely used by analyst, data miners and statisticians for the purpose of data analysis and developing statistical applications. R is an open source programming language that makes it highly popular among small and medium sized industries who use it for data exploration, data visualization, descriptive analysis and predictive analysis. R language offers many benefits to the business organizations such as developing statistical reports of the information, which plays a very important role in decision making process as it visualize the data in a simpler manner allowing the management to easily understand the market condition and customer behaviour. R is also a very user friendly programming language which can easily be integrated with other databases and also support various operating systems such as Windows, Mac OS and Linux.
This course serves immensely to candidates who wish to join corporate world and do good in roles that require Data Analysis, Machine Learning and Visualisation.
Reasons why you should learn R:
- R is a powerful yet user friendly statistical and data analysis tool used by millions of organizations. This would allow you to learn and master the tool with a little effort and forge a career relatively easy.
- R is free and open source programming language. There is a huge community for the R programming language where you can easily find relevant solutions to your issues.
- Professionals with knowledge of R are in demand across all businesses, no matter the size, scale or nature, needs of the organization. R is used to analyse and represent data in a visually engaging manner to support decision making process.
- Professionals with R programming skills are able to pursue plethora of job profiles such as Data Manager, Data Scientists, Data Analyst, Data Engineer etc.
- The average pay scale for a Data Analyst with knowledge of R is way higher than average pay scale of IT professionals.
USPs of Program:
- Our teaching methodologies include extensive use of Real-Life Projects and Case Studies which helps students to learn and understand real world problems and solutions.
- Our trainers have extensive professional experience from industries like Banking, Insurance, Consulting, Telecom etc. who mentor students for successful careers.
- Our teams provides 100% Placement Assistance to our students for successful careers.
- Learners will get thorough knowledge of the software and will be able to apply knowledge for problem solving.
- Learners from non-technical background will learn coding which increases employability.
- Learners will be able to undertake data exploration, data manipulation, data visualization, descriptive analysis and machine learning
- Learners will be job ready after successfully completing the program and can pursue career as Data Scientist, Data Engineer, Data Analyst, Business Analyst and much more.
All professionals and students who want to learn from the best institute for online training in Delhi, Noida, Mumbai, Bangalore, Kolkata, Pune etc. Every person who wants have a job/career in Analytics, Business Intelligence, Data Management, Actuarial Science or Research will benefit from this course.
- Gain a foundational understanding of business analytics
- 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 understanding of statistical concepts, hypothesis testing method and regression models.
- Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering
- Lectures 51
- Quizzes 0
- Duration 15+ hours
- Language English
- Students 196
- Assessments Yes
- R As Calculator
- Functions and Packages
- Matrices and Arrays
- Dataframes and DPLYR Package
- DPLYR Package
- If Condition Part 1
- If Condition Part 2
- Looping in R
- User Defined Functions in R
- Measures of Central Tendency
- Measures of Dispersion, Moments
- Counting Techniques
- Baiscs In Probability
- Random Variables
- Discrete Distributions
- Continuous Distributions Part 1
- Continuous Distributions Part 2
- Sampling Theory
- Hypothesis Testing
- Correlation and Regression
- t-Test in R
- Chi Square Test in R
- ANOVA One Way
- Two Sample t-Test in R
- ANOVA Two Way
- Z Population Proportions Test
- Introduction to Charts and Graphs in R
- GGPlot2 Part 1
- GGPlot2 Part 2
- GGPlot2 Part 3
- GGPlot Themes
- Corrplot and Corrgram
- Date Time Functions in R
- Tidyr Package
- Stringr Package
- Some Useful Functions in R
- Machine Learning:Linear regression: lm()
- Machine Learning:Linear Regression: Case Study
- Machine Learning:Logistic regression: glm()
- Machine Learning:Logistic regression Case Study
- Machine Learning: K Mean Clustering
- Machine Learning: Decision Tree
- Machine Learning: Neural Nets