CAREER TRACK

Data Scientist with R

A Data Scientist combines statistical and machine learning techniques with R programming to analyze and interpret complex data.

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R Language
94 hours
22 Courses
$118,000/year

1

Introduction to R

Master the basics of data analysis by manipulating common data structures such as vectors, matrices and data frames.

4 hours

Jonathan Cornelissen

Co-founder of DataCamp
2

Intermediate R

Continue your journey to become an R ninja by learning about conditional statements, loops, and vector functions.

6 hours

Filip Schouwenaars

Data Science Instructor at DataCamp
3

Introduction to the Tidyverse

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collect...

4 hours Play preview

David Robinson

Chief Data Scientist, DataCamp
4

Importing Data in R (Part 1)

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

3 hours

Filip Schouwenaars

Data Science Instructor at DataCamp
5

Importing Data in R (Part 2)

Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

3 hours

Filip Schouwenaars

Data Science Instructor at DataCamp
6

Cleaning Data in R

Learn to explore your data so you can properly clean and prepare it for analysis.

4 hours

Nick Carchedi

Product Manager at DataCamp
7

Introduction to Data

Learn the language of data, study types, sampling strategies, and experimental design.

4 hours Play preview

Mine Cetinkaya-Rundel

Associate Professor at Duke University & Data Scientist and Pr...
8

Intro to SQL for Data Science

Master the basics of querying tables in relational databases such as MySQL, Oracle, SQL Server, and PostgreSQL.

4 hours

Nick Carchedi

Product Manager at DataCamp
9

Introduction to Relational Databases in SQL

Learn how to create one of the most efficient ways of storing data - relational databases!

4 hours

Timo Grossenbacher

Data Journalist at SRF Data
10

Joining Data in SQL

Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.

5 hours Play preview

Chester Ismay

Data Science Evangelist at DataRobot
11

Introduction to Shell for Data Science

The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs ...

4 hours

Greg Wilson

Co-founder of Software Carpentry
12

Data Visualization with ggplot2 (Part 1)

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

5 hours

Rick Scavetta

Rick Scavetta is a co-founder of Scavetta Academy.
13

Communicating with Data in the Tidyverse

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communica...

4 hours

Timo Grossenbacher

Data Journalist at SRF Data
14

Visualization Best Practices in R

Learn to effectively convey your data with an overview of common charts, alternative visualization types, and percep...

4 hours

Nick Strayer

PhD Candidate, Biostatistics; Vanderbilt University
15

Exploratory Data Analysis

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

4 hours Play preview

Andrew Bray

Assistant Professor of Statistics at Reed College
16

Exploratory Data Analysis in R: Case Study

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

4 hours Play preview

David Robinson

Chief Data Scientist, DataCamp
17

Machine Learning Toolbox

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

4 hours

Zachary Deane-Mayer

Automation First Data Scientist at DataRobot
18

Correlation and Regression

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

4 hours Play preview

Ben Baumer

Assistant Professor at Smith College
19

Multiple and Logistic Regression

In this course you'll lear to add multiple variables to linear models and to use logistic regression for classification.

4 hours Play preview

Ben Baumer

Assistant Professor at Smith College
20

Machine Learning in the Tidyverse

Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models.

5 hours Play preview

Dmitriy Gorenshteyn

Lead Data Scientist at Memorial Sloan Kettering Cancer Center
21

Cluster Analysis in R

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract in...

4 hours Play preview

Dmitriy Gorenshteyn

Lead Data Scientist at Memorial Sloan Kettering Cancer Center
22

Unsupervised Learning in R

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

4 hours Play preview

Hank Roark

Senior Data Scientist, Boeing
Statement of accomplishment

See all 22 courses

Jonathan Cornelissen

Co-founder of DataCamp

Filip Schouwenaars

Data Science Instructor at DataCamp

David Robinson

Chief Data Scientist, DataCamp

Nick Carchedi

Product Manager at DataCamp

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Data Scientist with R

Introduction to R

Intermediate R

Introduction to the Tidyverse

Importing Data in R (Part 1)

Importing Data in R (Part 2)

Cleaning Data in R

Introduction to Data

Intro to SQL for Data Science

Introduction to Relational Databases in SQL

Joining Data in SQL

Introduction to Shell for Data Science

Data Visualization with ggplot2 (Part 1)

Communicating with Data in the Tidyverse

Visualization Best Practices in R

Exploratory Data Analysis

Exploratory Data Analysis in R: Case Study

Machine Learning Toolbox

Correlation and Regression

Multiple and Logistic Regression

Machine Learning in the Tidyverse

Cluster Analysis in R

Unsupervised Learning in R

Statement of accomplishment

Ready To Learn

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Courses

Tracks

Instructors

Data Scientist with R

Introduction to R

Intermediate R

Introduction to the Tidyverse

Importing Data in R (Part 1)

Importing Data in R (Part 2)

Cleaning Data in R

Introduction to Data

Intro to SQL for Data Science

Introduction to Relational Databases in SQL

Joining Data in SQL

Introduction to Shell for Data Science

Data Visualization with ggplot2 (Part 1)

Communicating with Data in the Tidyverse

Visualization Best Practices in R

Exploratory Data Analysis

Exploratory Data Analysis in R: Case Study

Machine Learning Toolbox

Correlation and Regression

Multiple and Logistic Regression

Machine Learning in the Tidyverse

Cluster Analysis in R

Unsupervised Learning in R

Statement of accomplishment

Ready To Learn