Hands on Machine learning & Data science with R- Over 10 projects

Features Includes:
  • Self-paced with Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App

Course Preview Video


Invest in yourself in 2020. Job market is changing like never before & without machine learning & data science skills in your cv/resume, you can't do much.

You will get everything you need to start your career as data scientist.

Learn machine learning fundamentals, applied statistics, R programming, data visualization with ggplot2, lattice and build machine learning models with R using rstudio.

More than 15 projects to build your portfolio, Code files included.

Unlike most machine learning courses out there, the Complete Machine Learning & Data Science with R is affordable and comprehensive. Here are some highlights of the program:

  • Machine learning fundamentals
  • Applied statistics for machine learning & data science
  • Visualization with R for machine learning
  • ANOVA Implementation with R
  • Linear regression with R
  • Logistic Regression with R
  • Dimension Reduction Technique
  • Tree-based machine learning techniques
  • KNN Implementation
  • Naïve Bayes
  • Neural network machine learning technique

Basic knowledge
  • Laptop/desktop/mobile phone with internet to watch videos
  • Laptop/desktop to practice your knowledge
  • Desire to learn machine learn

What will you learn
  • R programming
  • Applied statistics
  • Data visualization
  • Data wrangling
  • Machine learning models
  • Career guidance on data scientist roles and how to get into it
  • How to build your portfolio to show your skills
  • Over 15 projects to add to your portfolio
  • Quizzes and projects to sharpen your skills
Course Curriculum
Number of Lectures: 81 Total Duration: 12:43:48
Christopher Hekimian – November 25, 2020

I was impressed with every aspect of this course. I feel like I came away with the knowledge and experience of at least two college-level courses. Plus you learn R programming and end up with an R development environment. I would encourage anyone to take this course.