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Associate Data Scientist in R

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Learn how to use R for data science, from data manipulation to machine learning. Gain the career-building skills you need to succeed in data science!
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Track Description

Associate Data Scientist in R

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!

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to R

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

  • Course

    2

    Intermediate R

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

  • Course

    3

    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.

  • Project

    bonus

    Analyze the Popularity of Programming Languages

    Analyze the popularity of programming languages over time based on Stack Overflow data.

  • Course

    6

    Joining Data with dplyr

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

  • Course

    11

    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.

  • Course

    13

    Cleaning Data in R

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

  • Course

    20

    Introduction to Regression in R

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

  • Course

    23

    Sampling in R

    Master sampling to get more accurate statistics with less data.

  • Course

    24

    Hypothesis Testing in R

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

  • Course

    26

    Experimental Design in R

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

  • Course

    29

    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.

  • Course

    30

    Unsupervised Learning in R

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

Associate Data Scientist in R
22 Courses
Track
Complete

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