This complete course is the most popular and is designed for learners who want to go from zero to hero.
The course comprises modules that will help you become an expert in using R for Data Analysis and land any job you want.
This module covers all aspects of the beginner, intermediate and advanced series.
Beginner modules:
- Introduction to Programming for Data Analysis
- R vs Python – What You Need To Know
- Introduction to R
- Getting started with R and Common IDEs
- R and RStudio
- Data Analysis and Uses of R in the industry
- Initialising and Setting Up Projects in R
- Base R
- Arithmetic Operations and Logical Expressions
- Variable Assignment and Rstudio environment
- File naming conventions
- Data Types
- Object Types and Classes
- Data Import and export in R (Excel/CSV/TXT)
- Summary and Descriptive Tables
- Data Visualisation basics
- R Packages
- Case Study
- Portfolio Project
Intermediate modules:
- Introduction to tidyverse and pipping
- Other Data Sources
- Introduction to databases and SQL (connection – ODBC)
- Data Import and export in R
- Data Manipulation – Grouping, Summaries, Filter, Joining Data
- Exploratory (intermediate) data analysis – Summary Stats
- Data and Time in R
- Introduction to Strings and Regex
- Introduction to Data Visualisation with ggplot
- Functional Programming/control structures
- Case Study
- Portfolio Project
Advanced modules:
- Advanced data import
- Advanced data visualisation with ggplot
- Advanced Dates and Time
- Advanced Functions (The Apply Family)
- Advanced Data Manipulation
- Writing custom functions in R
- Reports with Markdown
- The Apply Family
- Data Analysis Project Planning & Efficient programming
- Efficient loading of packages
- File Management in R
- Utilising Git & GitHub (within the RStudio interface)
- Case Study
- Portfolio Project
