ZettaMine Labs Pvt. Ltd., 63/A, Rd Number 13, Giani Zail Singh Nagar, Film Nagar, Hyderabad, 500096

9121192119

info@nitwai.com

Sat-Sun: 9AM - 6PM

The R Toolkit

About the Workshops

Learn the fundamentals of the R Programming language, then apply it to statistical analysis, visualizations and machine learning. Learn Variables, Vectors, Matrices, loops, Functions, Packages, Plotting, K-Means clustering, Decision Trees and more

First Timers

This course teaches R from the basics, so no programming experience is required to take this class. That being said, you will benefit most if you already have a strong foundation in mathematics and statistics.

Junior Engineers

R is a great choice as a 2nd programming language. If you’re already well versed in a general-purpose language, then you’ll be able to appreciate how well-suited R is to statistical analysis and data science.

Senior Engineers

If you already have a strong foundation in R or Data Science in general, then this course may be review for you. Please review the curriculum below to make sure we’re covering topics that interest you.

Course Curriculum

41 Lectures, 10 Homeworks, 3 Large Projects

  • Introduction
  • Table of Contents
  • Download RStudio
  • Introduction to Variables – Part A
  • Introduction to Variables – Part B
  • Homework #1: Variables
  • Data Input – Part A
  • Data Input – Part B
  • Data Output
  • Homework #2: I/O
  • Loops
  • If Statements – Part A
  • If Statements – Part B
  • Homework #3: Control Flow
  • Vectors
  • Functions – Part A
  • Functions – Part B
  • Packages – Part A
  • Packages – Part B
  • Case Study – Part A
  • Case Study – Part B
  • Homework #4: Functions
  • Project #1
  • Introduction to Matrices
  • Homework #5: Matrices
  • Introduction to Data Frames – Part A
  • Introduction to Data Frames – Part B
  • Homework: #6: Data Frames
  • Introduction to Lists and lapply – Part A
  • Introduction to Lists and lapply – Part B
  • Homework #7: Lists
  • Data Manipulation and dplyr – Part A
  • Data Manipulation and dplyr – Part B
  • Data Manipulation and dplyr – Part C
  • Homework #8: Data Analysis
  • Basic Plots – Part A
  • Basic Plots – Part B
  • Additional Plotting – Part A
  • Additional Plotting – Part B
  • Advanced Plotting – Part A
  • Advanced Plotting – Part B
  • Homework #9: Visualizations
  • Project #2