An online course that is structured for all those who are interested to work in the Analytics industry and is also designed to further aid data analysts, business analysts, data engineers, data scientists, technical managers and entrepreneurs looking to understand R programming concepts.
A virtual online training course designed for those who are keen on working in the Analytics industry. This course will also help analysts – data or business, data scientists & engineers to keep abreast with this latest analytics tool that is R.
R is a computer programming language and software environment that is used for statistical computations. Besides this it is also used for supporting graphics developed by R Foundation for Statistical Computing. Today, R language is being used by majority of statisticians and data miners for the development of statistical software and data analysis.
Considering the popularity of R as an analytics tool among data scientists we have developed a Analytics with R curriculum. Since R – programming has become a major competitor for its contemporaries like SAS, SPSS, Strata and other prevalent Business Analytics packages our Analytics with R course will enable you to join one of the most favoured league in the Data Science arena. It’s your time to become an R –programming language expert by taking up Collabera TACT’s exclusive & live virtual learning training.
This online curriculum has been designed in such a way that it focuses on modules like Big Data Analytics with R. A person keen on working in the analytics field should definitely take up this course. Other than the freshers this Big Data Analytics with R course is also for experienced analysts who wish to keep themselves updated on R. Professionals like Business Analysts, Data Analysts, Data Engineers and people from the field of Data Science and entrepreneurs & managers from the field of technology are the ones who can benefit the most from this course.
This course will educate you on the concepts of R as programming language and its applications in the respective fields of work. Also it will help you lend a perspective on the present-day trends and its scope in future.
- What is Data science? Understanding the 4 V’s.
- What is Business Analytics?
- Understanding the data and defining the scope of Business Analytics
- What are Decision models
- Companies that use R
- Role of a data scientist
- History of R
- About R and R Studio
- Configuration required for R
- Data Types of R
4.1 Hands on – on R data Types
4.2 Simple Statistics using R
4.3 Grouping, Loops, Conditional Execution
- Importing data and connecting to database systems
- Merging, concatenating, reshaping data
- Using dplry package for data manipulation
- Write Functions
- Various types of visualization
- Using ggplot package
- Creating Graphs in R – Line plots, Bar charts, Pie charts, Histograms, density plots, Scatter plots
- Why study statistics
- Applications and types of statistics
- Population vs sample
- Types of data and statistical variables
- Summarize the data and making decisions using summary statistics
- Random Variables, Expected Value
- Probability Distribution
- Standard Deviation and Variance
- Types of Distributions
- Understanding Normal Distribution
- Skewness & Kurtosis
- Types of Sampling
- What is CLT and its application
- P-value, z score
- T-Distribution and Poisson distribution
- Null and Alternate hypothesis
- Type -1 , type-2 errors
2.1 Linear Regression
- Text Analytics
1 Moving Average / Holt Winter
- ARIMA / ARMA
- Use- Case