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 Courses
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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.
Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.
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.
Data Manipulation with dplyr
Delve further into the Tidyverse by learning to transform and manipulate data with dplyr.
Joining Data with dplyr
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Introduction to Statistics in R
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.
Introduction to Data Visualization with ggplot2
Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.
Intermediate Data Visualization with ggplot2
Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
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.
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.
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.
Working with Dates and Times in R
Learn the essentials of parsing, manipulating and computing with dates and times in R.
Introduction to Writing Functions in R
Take your R skills up a notch by learning to write efficient, reusable functions.
Exploratory Data Analysis in R
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
Introduction to Regression in R
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
Intermediate Regression in R
Learn to perform linear and logistic regression with multiple explanatory variables.
Hypothesis Testing in R
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
Experimental Design in R
In this course you'll learn about basic experimental design, a crucial part of any data analysis.
Supervised Learning in R: Classification
In this course you will learn the basics of machine learning for classification.
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.
Unsupervised Learning in R
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
Intermediate Importing Data in R
Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.
Machine Learning for Business
Understand the fundamentals of Machine Learning and how it's applied in the business world.
Introduction to SQL
Learn how to create and query relational databases using SQL in just two hours.
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!
Joining Data in SQL
Level up your SQL knowledge and learn to join tables together, apply relational set theory, and work with subqueries.
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