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Course Outline
Day One: Language Basics
- Course Introduction
- About Data Science
- Data Science Definition
- Process of Doing Data Science.
- Introducing R Language
- Variables and Types
- Control Structures (Loops / Conditionals)
- R Scalars, Vectors, and Matrices
- Defining R Vectors
- Matricies
- String and Text Manipulation
- Character data type
- File IO
- Lists
- Functions
- Introducing Functions
- Closures
- lapply/sapply functions
- DataFrames
- Labs for all sections
Day Two: Intermediate R Programming
- DataFrames and File I/O
- Reading data from files
- Data Preparation
- Built-in Datasets
- Visualization
- Graphics Package
- plot() / barplot() / hist() / boxplot() / scatter plot
- Heat Map
- ggplot2 package (qplot(), ggplot())
- Exploration With Dplyr
- Labs for all sections
Requirements
- Basic programming background is preferred
Audience
- Data analysts
14 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from £3800 online delivery, based on a group of 2 delegates, £1200 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses
Testimonials (2)
knowledge of the trainer, tailor based, all topics covered
eleni - EUAA
Course - Forecasting with R
The real life applications using Statcan and CER as examples.
