R language

R programming language start from zero knowledge, while it would help for better learning some programming or data knowledge. R programming language is considered as an easy to learng language, the R programming language is used to understand, interpret and visualize data. Nowadays companies and research institutions collect vast amount of data as well as more complex data, the R language is the chosen language for data analysis. The R language is used to do data analysis, scientific calculations and machine learning. With the right instructor training programming does not need to be difficult, programming is structured and logic. This training is 100% in practice “Hands On”. We learn by doing.

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Course Details

  • 🕒 Schedule: Twice a week, evenings only

  • ⏱️ Duration: 45 hours over 9 weeks

  • 💶 Price: €300

  • 👨‍🏫 Format: Instructor-led, hands-on training

  • 📦 Includes: Practical exercises, course materials, and expert feedback

About the course

R programming language start from zero knowledge, while it would help for better learning some programming or data knowledge. R programming language is considered as an easy to learng language, the R programming language is used to understand, interpret and visualize data. Nowadays companies and research institutions collect vast amount of data as well as more complex data, the R language is the chosen language for data analysis. The R language is used to do data analysis, scientific calculations and machine learning. With the right instructor training programming does not need to be difficult, programming is structured and logic. This training is 100% in practice “Hands On”. We learn by doing.

  • Introduction to R
    • Introduction
    • Installation

 

  • R Programming
    • R Operator
      • R Conditional Statement & Loop
      • If Else (Conditional Statement)
      • Nested If Else (Conditional Statement)
      • For Loop
      • While loop
      • Ect

 

  •  R Function
    • Numeric Functions (sqrt(), floor(), ect..)
    • Statistical Functions (mean(), meadian(), sd() ect..)
    • Creating our own Functions
    • R Data Structure
      • Vector
      • Matrix, Array, Data Frame
      • Factor
      • List

 

  • Import and Export in R
      • Import CSV Data in R
      • Import Text Data in R
      • Import Excel, Database and Web Data in R
      • Export Data – Text,
      • Export Data – CSV, Excel

 Data Manipulation in R

  • Apply Functions
    • Apply()
    • Lapply()
    • Sapply()
    • Tapply()
    • ect
  • Dplyr Package – base commands
  • Dplyr Package
    • Mutate
    • Filter
    • Arrange
    • ect
  • Dplyr Package –
    • Summarise ()
    • Pipe operator: %>%
    • Group by ()

 * Different Date format

  •      Data Visualisation
      • Scatter Plot
      • Line Chart
      • Bar Plot
      • Pie Chart
      • Histogram
      • Ggplot2 Package

 Introduction to Statistics

    • Typo of Statistics
    • Bias
    • Cluster Sampling
    • Systematic Sampling
  •  Statistics
  • Quantitative and Qualitative data
  • Descriptive statistics
  •  Distribution
  •  Mean
  • Standard Deviation
    • Formula
  • Types of Distributions
  • Normal distribution
  • Functions in R
  • Testing Hypothesis
    • Null Hypothesis
    • Alternative Hypothesis
    • Hypothesis Test – Outcome
  • Anova
  • Chi Square
  • Introduction to Machine Learning with R
  • Machine Learning with R
    • Linear Regression
    • Logistic Regression
    • K Nearest Neighbors
    • K-Means Clustering
    • Neural Networks
    • Natural Language Processing
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