Data Analyst in R (Dataquest)

Offered by Dataquest,
Data Analyst in R (Dataquest)

Equip yourself with the necessary R skills to land your first job as a data analyst — or take your career to the next level by adding this in-demand programming language.
You’ll learn how to program with R to explore and extract data and create data visualizations. By the end, you’ll be able to present insights thanks to deep statistical analysis.

In this path, you’ll learn the fundamentals of R and build upon them with more advanced skills. You’ll learn how to use RStudio, applications and tools, tidyverse, DataFrames, tibbles, operators, expressions, and much more — as well as data visualization, graphs, plots, and charts.
Best of all, you’ll learn by doing — you’ll write code and get feedback directly in the browser. You’ll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview.

  • Introduction to Data Analysis in R
  • Data Structures in R
  • Control Flow, Iteration, and Functions in R
  • Specialized Data Processing in R: Strings and Dates
  • Data Visualization in R
  • Data Cleaning in R
  • Storytelling Through Data Visualization in R
  • Data Cleaning in R: Advanced
  • SQL Fundamentals
  • SQL Intermediate in R
  • APIs in R
  • Web Scraping in R
  • Statistics Fundamentals for R Users
  • Statistics Intermediate in R: Averages and Variability
  • Probability Fundamentals for R Users
  • Hypothesis Testing in R
  • Conditional Probability in R
  • Linear Modeling in R
  • Introduction to Machine Learning
  • Introduction to Shiny in R
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Computer Science: Programming with a Purpose (Coursera) Coursera
Princeton University

Computer Science: Programming with a Purpose (Coursera)

The basis for education in the last millennium was “reading, writing, and arithmetic;” now it is reading, writing, and computing. Learning to program is an essential part of the education of every student, not just in the sciences and engineering, but in the arts, social sciences, and humanities, as well. Beyond direct applications, it is the first step in understanding the nature of computer science’s undeniable impact on the modern world.

Nov 2nd 2026
5-12 Weeks
Principles of Computing (Part 2) (Coursera) Coursera
Rice University

Principles of Computing (Part 2) (Coursera)

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Understanding these principles is crucial to the process of creating efficient and well-structured solutions for computational problems. To get hands-on experience working with these concepts, we will use the Python programming language. The main focus of the class will be weekly mini-projects that build upon the mathematical and programming principles that are taught in the class.

Nov 2nd 2026
4 Weeks
Improving your statistical inferences (Coursera) Coursera
Eindhoven University of Technology

Improving your statistical inferences (Coursera)

This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power.

Nov 2nd 2026
5-12 Weeks
Data Scientist in Python (Dataquest) Dataquest
Dataquest

Data Scientist in Python (Dataquest)

Gain the Python skills you need to start and grow your career as a data scientist. You’ll learn to create data visualizations, perform web-scraping, build machine learning algorithms, and much more. By the end, you’ll be able to analyze datasets, help make business decisions, and use machine learning to solve complex problems.

Self Paced
Self-Paced
Business Applications of Hypothesis Testing and Confidence Interval Estimation (Coursera) Coursera
Rice University

Business Applications of Hypothesis Testing and Confidence Interval Estimation (Coursera)

Confidence intervals and Hypothesis tests are very important tools in the Business Statistics toolbox. A mastery over these topics will help enhance your business decision making and allow you to understand and measure the extent of ‘risk’ or ‘uncertainty’ in various business processes. This course advances your knowledge about Business Statistics by introducing you to Confidence Intervals and Hypothesis Testing. These are done by easy to understand applications.

Nov 2nd 2026
4 Weeks
Practical Time Series Analysis (Coursera) Coursera
The State University of New York

Practical Time Series Analysis (Coursera)

Many of us are "accidental" data analysts. We trained in the sciences, business, or engineering and then found ourselves confronted with data for which we have no formal analytic training. This course is designed for people with some technical competencies who would like more than a "cookbook" approach, but who still need to concentrate on the routine sorts of presentation and analysis that deepen the understanding of our professional topics.

Nov 2nd 2026
5-12 Weeks
Data Analyst in Python (Dataquest) Dataquest
Dataquest

Data Analyst in Python (Dataquest)

Gain the practical Python skills that will help you land your first job as a data analyst — or help you grow your career by adding one of the most popular programming languages to your CV. You’ll learn how to program with Python to dig into data analysis and data visualization — among other things. By the end, you’ll be able to manage the entire analysis process from preparing data to presenting insights through data visualization.

Self Paced
Self-Paced