Free course on machine learning with R

FAQs

• What are the prerequisites to get started with Machine Learning with R?

  There are no prerequisites to learn Machine Learning with R. However, it is recommended that learners have a basic understanding of mathematics, statistics and programming.

• How do beginners get started with the Machine Learning with R free course?

  Beginners who want to learn Machine Learning with R can start with the fundamentals first. Once you have mastered the basics you can move on to the advanced topics.

• How long does it take to finish the Introduction to Machine Learning with R?

  The Introduction to Machine Learning with R course consists of 10 hours of video content that will help you gain a thorough understanding.
   

• Is Machine Learning with R easy to learn?

  The videos that you find as a part of the Introduction to Machine Learning with R course are created by mentors who are industry leaders with vast experience in the field. They are aware of the needs of different learners and have designed the course to be easy to learn.
   

• Can I complete this Machine Learning with R course in 90 days?

  Yes, you can complete the Machine Learning with R course within 90 days.
   

• Will I get a certificate after completing the free Machine Learning with R course?

  Yes, You will receive a Course Completion Certificate from SkillUp upon completing the free Machine Learning with R program. You can unlock it by logging in to your SkillUp account. As soon as the certificate is unlocked, you will receive a mail with a link to your SkillUp learning dashboard on your registered mail address. Click the link to view and download your certificate. You can even add the certificate to your resume and share it on social media platforms.

• What are my next best learning options after completing this free Machine Learning with R course?

  After completing this free Machine Learning with R course, you can opt for the Post Graduate Program in AI and Machine Learning provided by Simplilearn.

• What are the career opportunities after completing the Machine Learning with R course?

  Common careers after this course include:

  • ML Engineer
  • Analytics Manager
  • Business Analyst
  • Information Architect
  • Developer

• Why learn Machine Learning with R?

  Machine Learning (ML) is the technology that has revolutionized the way we live in the 21st century.  Self-driving cars, cyber fraud detection, and online recommendation engines from Facebook, Spotify, Netflix, and Amazon are all applications of machine learning. According to a recent report from TMR, MLaaS (Machine learning as a Service) is expected to grow to $19.9 billion by the end of 2025. Almost every customer-centric organization today is en route to AI adoption in some form or another. This has led to a simultaneous surge in the demand for trained machine learning engineers across top enterprises worldwide — meaning that now is the time to learn machine learning.

• How is R used in Machine Learning?

  R, its packages and functions, are used in Machine Learning for the building and exploration of one-off models. The R interactive environment is good while working with new problems.

• What are the top skills required for a career in Machine Learning?

  The top skills required for a career in Machine Learning are:

  • Computational and Statistical awareness
  • Basics of programming
  • Data modelling
  • Neural networks and machine learning algorithms 

• What are the basics covered in this Machine Learning with R course?

  The basics covered in the machine learning with R course are:

  • Machine Learning Basics
  • Hierarchical Clustering in R
  • Time Series Analysis in R
  • R programming basics
  • Linear Regression in R
  • Logistic Regression in R
  • Decision Tree in R
  • Random Forest in R
  • Support Vector Machine in R

• Are there any Machine Learning books for beginners to refer to along with this free course?

  Below are Machine Learning with R books you can refer:

  • The Hundred-Page Machine Learning Book
  • Machine Learning: The New AI
  • The Elements of Statistical Learning
  • Machine Learning in Action
  • Machine Learning: A Technical Approach To Machine Learning for Beginners