Data Scientist Professional with R

Master the skills you need to pass the Data Scientist Professional with R certification and prepare yourself for success in the field of data science. As you progress through the courses in this track, you will focus on using R for data science. You will explore how learning data science with R can help you to import, clean, manipulate, and visualize data, and develop a solid foundation for your data science journey. You’ll cover a range of different skills, including data manipulation, visualization, and analysis, using popular R packages like ggplot2, dplyr, and readr. You will work with real-world datasets as you write your own functions and learn foundational statistical and machine learning techniques. You will also gain an understanding of SQL for relational databases and Git for data science projects, two essential tools for any data scientist. Through interactive exercises, you will get hands-on experience with R programming and the popular packages used in the field of data science. Completing this track will give you the knowledge and experience necessary to confidently pass the Data Scientist Professional with R certification and thrive as a data scientist.

R107 hours28 coursesStatement of Accomplishment

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Introduction to R

Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

4 hours

Intermediate R

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

6 hours

Introduction to the Tidyverse

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.

4 hours

Data Manipulation with dplyr

Delve further into the Tidyverse by learning to transform and manipulate data with dplyr.

4 hours

Joining Data with dplyr

Learn to combine data across multiple tables to answer more complex questions with dplyr.

4 hours

Introduction to Statistics in R

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

4 hours

Introduction to Data Visualization with ggplot2

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

4 hours

Intermediate Data Visualization with ggplot2

Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.

4 hours

Data Manipulation with R

Data Communication Concepts

No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.

3 hours

Introduction to Importing Data in R

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

3 hours

Cleaning Data in R

Learn to clean data as quickly and accurately as possible to help your business move from raw data to awesome insights.

4 hours

Working with Dates and Times in R

Learn the essentials of parsing, manipulating and computing with dates and times in R.

4 hours

Importing & Cleaning Data with R

Introduction to Writing Functions in R

Take your R skills up a notch by learning to write efficient, reusable functions.

4 hours

R Programming

Exploratory Data Analysis in R

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

4 hours

Introduction to Regression in R

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

4 hours

Intermediate Regression in R

Learn to perform linear and logistic regression with multiple explanatory variables.

4 hours

Sampling in R

Master sampling to get more accurate statistics with less data.

4 hours

Hypothesis Testing in R

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

4 hours

Experimental Design in R

In this course you'll learn about basic experimental design, a crucial part of any data analysis.

4 hours

Statistics Fundamentals with R

Supervised Learning in R: Classification

In this course you will learn the basics of machine learning for classification.

4 hours

Supervised Learning in R: Regression

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

4 hours

Unsupervised Learning in R

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

4 hours

Intermediate Importing Data in R

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

3 hours

Machine Learning for Business

Understand the fundamentals of Machine Learning and how it's applied in the business world.

2 hours

Introduction to SQL

Learn how to create and query relational databases using SQL in just two hours.

2 hours

Intermediate SQL

Accompanied at every step with hands-on practice queries, this course teaches you everything you need to know to analyze data using your own SQL code today!

4 hours

Joining Data in SQL

Level up your SQL knowledge and learn to join tables together, apply relational set theory, and work with subqueries.

4 hours

Introduction to Git

Familiarize yourself with Git for version control. Explore how to track, compare, modify, and revert files, as well as collaborate with colleagues using Git.

4 hours

Certification available

Prepare for certification by completing this track, or target the lessons you need with a personal learning plan.

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Data Scientist Professional with R

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Join over 12,770,000 learners and start Data Scientist Professional with R today!