2 months/20 Hour                                                   Price:85,000

                                                                                       80,000 

                                      

RStudio

This course aims to cover the fundamental aspects of RStudio, whilst also providing some practical examples of how to use RStudio in a data science use case. This course provides varied difficulty of material to test whether the concepts covered in the lectures have been understood and can be applied.    

What you’ll learn

1. Fundamentals of R Studio
2. Data Preparation within R Studio
3. Create Visualisations within R Studio
4. Build Working Functions
5. Work With Loops Such As For, If, Ifelse & While
6. Data Science

Course Content:

Module 1: Introduction to R and RStudio

1. Installing R and RStudio
2. Download and install R from CRAN.
3. Download and install RStudio.
4. Getting Started with RStudio
5. Overview of the RStudio interface.
6. Customizing RStudio settings.
7. Navigating the Source, Console, Environment/History, and Files/Plots/Packages/Help panes.

Module 2: Basic R Programming Refresher

1. Basic R Syntax
2. Variables and data types.
3. Basic operations and functions.
4. Data Structures in R
5. Vectors, matrices, lists, and data frames.
6. Basic Data Manipulation
7. Subsetting and indexing.
8. Basic data manipulation with base R functions.

Module 3: Working with RStudio

1. Projects in RStudio
2. Creating and managing projects.
3. Setting working directories.
4. Script Management\
5. Creating, saving, and sourcing R scripts.
6. Organizing scripts within a project.

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Module 4: Data Import and Export

1. Reading Data into R
2. Reading CSV, Excel, and other data formats.
3. Using read.csv(), read.table(), and packages like readxl and data.table.
4. Writing Data from R
5. Writing data to CSV and other formats using write.csv().
6. Exporting data with packages like writexl.

Module 5: Data Manipulation with dplyr

1. Introduction to dplyr
2. Installing and loading dplyr.
3. Basic functions: filter(), select(), mutate(), arrange(), and summarize().
4. Advanced-Data Manipulation
5. Grouping data with group_by().
6. Chaining operations with the pipe operator %>%.

Module 6: Data Visualization with ggplot2

1. Introduction to ggplot2
2. Installing and loading ggplot2.
3. Basic components: aesthetics, germs, and themes.
4. Creating Basic Plots
5. Scatter plots, line charts, and bar charts.
6. Advanced Plotting Techniques
7. Faceting, customizing themes, and adding annotations.

Module 7: RMarkdown and Reproducible Research

1. Introduction to RMarkdown
2. Creating RMarkdown documents.
3. YAML header, markdown syntax, and code chunks.
4. Generating Reports
5. Rendering HTML, PDF, and Word documents.
6. Customizing document appearance with themes and templates.

Module 8: Statistical Analysis in RStudio

1. Basic Statistical Functions
2. Descriptive statistics: mean, median, mode, variance, and standard deviation.
3. Hypothesis testing: t-tests, chi-squared tests.
4. Regression Analysis
5. Linear regression with lm().
6. Interpreting regression outputs.

Module 9: Working with Git and Version Control

1. Introduction to Git
2. Setting up Git in RStudio.
3. Basic Git commands: clone, commit, push, pull.
4. Version Control in RStudio
5. Using the Git tab in RStudio.
6. Managing repositories and collaboration.

Module 10: Advanced RStudio Features

1. Debugging and Profiling
2. Using the RStudio debugger.
3. Profiling code performance.
4. Creating Shiny Apps
5. Introduction to Shiny.
6. The basic structure of a Shiny app.
7. Deploying Shiny apps.

Module 11: Best Practices and Resources

1. Coding Best Practices
2. Writing clean and efficient code.
3. Documenting and commenting code.
4. Resources for Further Learning
5. Online resources, books, and communities.
6. Advanced courses and certifications.

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International Student Fees: 400USD$

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Job Interview Preparation  (Soft Skills Questions & Answers)

• Tough Open-Ended Job Interview Questions
• What to Wear for Best Job Interview Attire
• Job Interview Question- What are You Passionate About?
• How to Prepare for a Job Promotion Interview

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Internships, Freelance and Full-Time Work opportunities

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Flexible Class Options

Week End Classes For Professionals  SAT | SUN

Corporate Group TrainingAvailable

Online Classes – Live Virtual Class (L.V.C), Online Training

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