Machine Learning R

Data Science

Course Description

This Machine Learning with R course dives into the basics of machine learning using an approachable, and well-known, programming language. You’ll learn about Supervised vs Unsupervised Learning, look into how Statistical Modelling relates to Machine Learning, and do a comparison of each.

6 Days

  • Analyze data find relative patterns to predict outcomes
  • Analyze continuous data in varying scenarios
  • Analyze and find patterns in data by applying various techniques
  • Expert in Confirmatory Data analysis
  • Analyze continuous data by applying various testing, regression and correlation scenarios
  • Implement key components specific to text mining and analytics aided by the real world datasets and text mining
  • Demonstrate expert knowledge in predicting outcomes

  • Who are familiar with R and looking for some advanced topics.
  • No prior programming knowledge is needed.

  • Genuine Interest in statistical programming
  • Computer ready to run R and RStudi
  • Basic understanding of statistics and data structure
  • NO prior knowledge in programming is required!

  • Day 1

    • Introduction to Analytics
    • Data Description

     

    Day 2

    • Basic R
    • Data Preprocessing

     

    Day 3

    • Linear Regression Model
    • Logistic Regression
    • K Nearest Neighbours Algorithm for Classification

     

    Day 4

    • Naïve Bayes Algorithm
    • Decision Tree

     

    Day 5

    • Random Forests
    • Support Vector Machines with case study
    • Unsupervised Learning – Clustering

     

     

    Day 6

    • Association Rule Mining
    • Time Series
    • Discussion on Application of Algorithms