The "Certified R Developer" course is aimed to train individuals in the fundamentals of R programming language, an open-source scripting language for predictive analytics and data visualization. Through a problem-solving based approach with hands-on projects and exams, this course intends to assist learners in becoming adept in manipulating, analyzing, and visualizing data using R.
This cybersecurity training covers data types and structures, data manipulation, statistics, data visualization, flow control, debugging tools, and statistical modelling in R. The course also addresses the use of R in big data analytics and its growing prominence as a challenge to more conventional statistical platforms.
Training Duration: 3 Days
- Certificate Of Completion Available
- Group Private Class
- VILT Class Available
- SBL-Khas Claimable
The R programming language is an open source scripting language for predictive analytics and data visualization. R is growing into one of the most popular and in-demand analytics tool given its open-source & free nature, advanced analysis and visualization abilities.
Benefits of learning R with us:
- Become proficient in manipulating, analyzing and visualizing data through the powerful R language
- Relevant examples and case studies make the learning more effective and easier
- Gain hands-on knowledge through the problem solving based approach of the course along with working on assignments and solving quizzes.
Today, R is being adopted by enterprise users for big data analytics and is increasingly being seen as a challenger to more traditional statistical and advanced analytic platforms.
- Understand the basics of the R programming language and its capabilities for predictive analytics and data visualization
- Learn how to manipulate, analyze, and visualize data using R
- Gain hands-on knowledge through problem solving and working on assignments and quizzes
- Learn about the various data types and data structures in R
- Learn how to read and write data from various sources, including tabular data files and csv files
- Learn how to perform basic statistics and statistical tests in R
- Learn about data visualization techniques in R, including creating bar charts, scatter plots, and histograms
- Learn about data manipulation techniques in R, including merging dataframes, handling missing values and outliers, and data aggregation
- Learn about the concepts of flow control, debugging tools, and functions in R
- Learn about statistical modeling in R, including simple linear regression, multiple regression, logistic regression, clustering and PCA
- Learn how to apply R in big data analytics and how it is increasingly being seen as a challenger to more traditional statistical and advanced analytic platforms.
None, anyone who is ready to start their Career in Analytics & Data Science can join.
New to cybersecurity? Consider opting for CSAU: Certified Security Aware User which is esigned to train learners on the most recent cyber threats and how to defend against them
Module 1: Introduction to R
- What is R ?
- Downloading and Installing R
- Introduction to the R UI
- Packages Management
Module 2: Data & Data Types in R
- Data Types
- Reading and Writing data
- Reading tabular data files
- Reading from csv files
- Creating a vector and vector operations
- Initializing a data frame
- Control structures
- Selecting data frames by position and name
- Changing directories
Module 3: Statistics in R
- Computing basic statistics
- Comparing means of two samples
- Testing a correlation for significance
- Testing a proportion
- Classical tests (t,z,F)
- Summarizing Data
- Cross tabulation
Module 4: R Data Visualization
- Creating a bar chart, dot plot
- Creating a scatter plot, pie chart
- Creating a histogram and box plot
- Other plotting functions
- Plotting with base graphics
- Plotting with Lattice graphics
- Plotting and coloring in R
Module 5: Data Manipulation in R
- Appending data to a vector
- Combining multiple vectors
- List management
- Merging dataframes
- Data transformation
- Strings and dates
- Outlier detection
- Handling NAs and Missing Values
- Matrices and Arrays
- Logical operations
- Relational operators
- Accessing Variables
- Matrix Multiplication and Inversion
- Managing Subset of data
- Character manipulation
- Data aggregation
Module 6: Functions and Programming in R
- Flow Control: For loop
- If condition
- While conditions and repeat loop
- Debugging tools
- Concatenation of Data
- Combining Vars, cbind, rbind
- Sapply, apply, tapply functions
Module 7: Statistical Modelling in R
- Simple linear regression
- Multiple Regression model
- Logistic regression
- Hierarchical Clustering
- K-Means Clustering
- PCA for Dimensionality Reduction
Certified R Developer
Exam Format : Multiple Choice Question (MCQ)
Exam Questions : 25 Questions
Exam Duration is : 90 Minutes
Exam Pass Mark : 70%
Exam Fees : Inclusive in the Course Fees
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