Overview
## Become a Data Scientist with R
Master the essential skills to launch your data science career using R, the popular programming language for statistical computing and data analysis. In this comprehensive Track, you'll learn how to import, clean, manipulate, visualize and model data using R's powerful packages and libraries. Gain hands-on experience with real-world datasets as you progress from the basics of R programming to advanced statistical and machine learning techniques.
## Develop a Strong Foundation in R for Data Science
Through interactive exercises and projects, you'll learn to:
* Work with data structures like vectors, lists, and data frames
* Write efficient and reusable R functions
* Wrangle and clean data using the tidyverse collection of packages
* Create compelling visualizations with ggplot2
* Apply statistical concepts like hypothesis testing and regression analysis
* Build and evaluate machine learning models for classification and prediction
## Learn from Industry Experts and Real-World Datasets
Benefit from the expertise of DataCamp's instructors, including data scientists, statisticians, and R practitioners from top companies and universities. You'll work with diverse, real-world datasets from various domains, such as finance, marketing, and healthcare, ensuring that you develop practical skills that are immediately applicable in the workplace.
## Prepare for the Associate Data Scientist Certification
This Track is designed to help you confidently pass the Associate Data Scientist in R certification exam. By completing the courses and projects, you'll gain a deep understanding of the key concepts and techniques covered in the certification syllabus. The Track also includes skill assessments to test your knowledge and identify areas for improvement.
## Advance Your Career with In-Demand R Skills
R is widely used across industries for data analysis, visualization, and machine learning. By mastering R, you'll open up a wide range of career opportunities, including data scientist, data analyst, statistician, and researcher roles. The skills you'll learn in this Track are highly sought after by employers and will help you stand out in the job market.
## Start Your Journey to Becoming a Certified R Data Scientist
Whether you're a complete beginner or have some experience with R, this Track will help you take your skills to the next level. By the end of the Track, you'll have a portfolio of projects demonstrating your ability to solve real-world data science problems using R. Start your journey today and become a certified Associate Data Scientist in R!
Syllabus
- Introduction to R
- Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.
- Intermediate R
- 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
- Build Tidyverse skills by learning how to transform and manipulate data with dplyr.
- Analyze the Popularity of Programming Languages
- 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 you move from raw data to awesome insights.
- Exploring Airbnb Market Trends
- 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.
- Modeling Car Insurance Claim Outcomes
- Intermediate Regression in R
- Learn to perform linear and logistic regression with multiple explanatory variables.
- Sampling in R
- Master sampling to get more accurate statistics with less data.
- Hypothesis Testing in R
- Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
- Hypothesis Testing with Men's and Women's Soccer Matches
- 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.
Taught by
Jonathan Cornelissen, Filip Schouwenaars, Andrew Bray, Hank Roark, Brett Lantz, John Mount, Nina Zumel, David Robinson, Charlotte Wickham, Joanne Xiong, James Chapman, Richie Cotton, Rick Scavetta, DataCamp Content Creator, Maggie Matsui, and Hadrien Lacroix