The R Programming Language

Learn one of the core programming languages of Data Science and AI

R is a powerful and versatile tool for data science, widely used by AI experts and data scientists alike. Its extensive libraries, vast user community, and open-source nature make it an indispensable resource for data analysis. This introductory course will provide you with the foundational skills and knowledge necessary to utilize R's powerful capabilities for data exploration, manipulation, and visualization. Through hands-on exercises and real-world examples, you will gain proficiency in R's syntax, data structures, and core functionalities, enabling you to tackle a wide range of data science challenges.

Course curriculum

  • 1

    Welcome and Prequesites

    • A Short History of the R Programming Languageson

    • Lesson 2: Installing and Setting Up R

    • Setting Up Jupyter Notebooks

    • Meet Your Instructor - Lee Medoff

  • 2

    Lesson 1: Introduction to R

    • Introduction to R

    • Lesson 1 Juypter Notebook - Introduction to R

  • 3

    Lesson 2: Working with Data Types

    • Data Structures in R

    • Lesson 2 Jupyter Notebook - R Data Structures

  • 4

    Lesson 3: Data Manipulation

    • Lesson 3: Data Munging with R

    • Lesson 3 Jupyter Notebook - Data Munging in R

  • 5

    Lesson 4: R Programming Basics

    • Lesson 4: R Programming Basics - Functions and Iteration

    • Lesson 4 Jupyter Notebook - R Programming Basics

  • 6

    Lesson 5: Exploratory Data Analysis (EDA) in R

    • Lesson 5: Exploratory Data Analysis (EDA) in R

    • Lesson 5 Jupyter Notebook - Exploratory Data Analysis (EDA) in R

  • 7

    Lesson 6: Introduction to R Studio

    • New LesLesson 6: R Studio - Introduction

  • 8

    Notebook Exercise Solutions

    • Juypter Notebook Exercise solutions

Lee Medoff

Meet Your Expert Instructor


Lee Medoff has 20 years of professional experience in banking and finance. He began his career as a desk quant at JPMorgan Chase, where he developed models to optimize the return on the bank’s card portfolio. Following the merger of JPMC and BankOne, he moved to the Models and Methodologies group of the Federal Reserve Bank of New York.  

After the Fed he joined Moody’s Analytics Risk Management Services, where he oversaw analytics teams in New York and India developing and customizing models for the company's proprietary software.  He then became a consultant in the Quantitative Advisory Services Group of EY’s Financial Services Risk Management practice, where he led consulting engagement teams to develop and validate models in the Risk Management space. He is currently the Head of Model Governance at Fifth Third Bank, a position he has held since 2021.


He holds advanced degrees in Statistics from Columbia University and Economics from New York University, and since 2019 has been an adjunct instructor teaching AI/ML, Python and data visualization at Sacred Heart University in Fairfield, Connecticut. In his spare time he enjoys cycling. He is an avid reader and a dedicated amateur chef.


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Unleash the power of R and transform into a data-driven decision-maker!