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Machine Learning in R

Duration: One Day Course

Prerequisite: Familiarity with programming and statistics.

R is the one of the most popular machine learning tools in use today. This course focuses on introducing concepts in machine learning and applying them in practical ways using R. Topics include R data manipulation, data structures, R graphics, exploratory data analysis, basic statistics, and introduction to regression and classification modeling. Participants will complete exercises to solidify understanding and build skills with the intent of finishing the course with a toolkit that can be leveraged in building R machine learning skills.

You Will Learn How To

  • Configure the RStudio environment and load packages
  • Use R basics such as basic math, data types, vectors, and calling functions
  • Use advanced data structures such as data frames, lists, and matrices
  • Use R base graphic packages
  • Perform exploratory data analysis
  • Use R to support basic statistics, correlation, and covariance
  • Use linear models such as linear regression and logistic regression
  • Use models such as decision trees, random forest, and K nearest neighbor

Geared To

  • Those interested in getting a thorough primer to machine learning and become proficient in introductory R programming

Contact Us to Get Started Today


Yvonne Baho

Yvonne M. Baho Director, Enterprise Learning
Phone: 978.582.7105


"The instructor was very responsive to input from the class and adapted to meet the needs specific to our context. I especially appreciated the many case studies and focus on assessment."

S. Bessias UNC Healthcare

"Very good overall view of DW concepts and provided valuable insight for such a varied audience."

Jerry Bundt Nestle Purina

"This was the best training class I’ve had in my 20 year career."

Tim Grieb Seattle Children’s Hospital

"The instructor did an excellent job and demonstrated an understanding of real world applications."

Sean Dewulf Con-way Freight


Yvonne Baho Yvonne M. Baho
Director, Enterprise Learning
Phone: 978.582.7105
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