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Programming for Data Science with R

Nanodegree Program

Prepare for a data science career by learning the fundamental data programming tools: R, SQL, command line, and git.

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  • Estimated time
    3 Months

    At 10 hrs/week

  • Enroll by
    May 31, 2023

    Get access to classroom immediately on enrollment

  • Skills acquired
    Git, Control Flow in R, SQL Queries, SQL JOINs, SQL Aggregations
In collaboration with
  • Mode

What you will learn

  1. Learn to Code with R and SQL

    3 months to complete

    Learn the programming fundamentals required for a career in data science. By the end of the program, you will be able to use R, SQL, Command Line, and Git.

    Prerequisite knowledge

    There are no prerequisites for this program, aside from basic computer skills.

    1. Introduction to SQL

      Learn SQL fundamentals such as JOINs, Aggregations, and Subqueries. Learn how to use SQL to answer complex business problems.

    2. Introduction to R Programming

      Learn R programming fundamentals such as data structures, variables, loops, and functions. Learn to visualize data in the popular data visualization library ggplot2.

    3. Introduction to Version Control

      Learn how to use version control and share your work with other people in the data science industry.

All our programs include

  • Real-world projects from industry experts

    With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

  • Real-time support

    On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.

  • Career services

    You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.

  • Flexible learning program

    Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

Program offerings

  • Class content

    • Content co-created with Mode
    • Real-world projects
    • Project reviews
    • Project feedback from experienced reviewers
  • Student services

    • Student community
    • Real-time support
  • Career services

    • Github review
    • Linkedin profile optimization

Succeed with personalized services.

We provide services customized for your needs at every step of your learning journey to ensure your success.

Get timely feedback on your projects.

  • Personalized feedback
  • Unlimited submissions and feedback loops
  • Practical tips and industry best practices
  • Additional suggested resources to improve
  • 1,400+

    project reviewers

  • 2.7M

    projects reviewed

  • 88/100

    reviewer rating

  • 1.1 hours

    avg project review turnaround time

Learn with the best.

Learn with the best.

  • Josh Bernhard

    Data Scientist at Nerd Wallet

    Josh has been sharing his passion for data for nearly a decade at all levels of university, and as Lead Data Science Instructor at Galvanize. He's used data science for work ranging from cancer research to process automation.

  • Derek Steer

    CEO at Mode

    Derek is the CEO of Mode Analytics. He developed an analytical foundation at Facebook and Yammer and is passionate about sharing it with future analysts. He authored SQL School and is a mentor at Insight Data Science.

  • Juno Lee

    Curriculum Lead at Udacity

    Juno is the curriculum lead for the School of Data Science. She has been sharing her passion for data and teaching, building several courses at Udacity. As a data scientist, she built recommendation engines, computer vision and NLP models, and tools to analyze user behavior.

  • Richard Kalehoff

    Instructor

    Richard is a Course Developer with a passion for teaching. He has a degree in computer science, and first worked for a nonprofit doing everything from front end web development, to backend programming, to database and server management.

  • Karl Krueger

    Command Line Instructor

    Before joining Udacity, Karl was a Site Reliability Engineer (SRE) at Google for eight years, building automation and monitoring to keep the world's busiest web services online.

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Programming for Data Science with R

Get started today

    • Learn

      You'll complete three projects, with a focus on the R Language.

    • Average Time

      On average, successful students take 3 months to complete this program.

    • Benefits include

      • Real-world projects from industry experts
      • Real-time classroom support
      • Career services

    Program details

    Program overview: Why should I take this program?
    • Why should I enroll?

      The Programming for Data Science Nanodegree program offers you the opportunity to learn the most important programming languages used by data scientists today. Get your start into the fascinating field of data science and learn R, SQL, terminal, and git with the help of experienced instructors.

    • What jobs will this program prepare me for?

      This is an introductory program that is not designed to prepare you for a specific job. However, as a graduate of this program, you will be proficient in the programming skills used in many data analysis and data science roles, including R, SQL, Terminal, and Git.

    • How do I know if this program is right for me?

      If you are interested in taking the first step into the field of Data Science this course is for you. This course will quickly teach you the foundational data science programming tools (R, SQL, Git). This course requires no pre-requisite knowledge so you can get started now. Having mastered these in demand tools, you will be able to tackle real world data analysis problems.

      Learning to program R and SQL, the main programing languages used by data scientists and analysts, is the core of this program. By learning these foundational programming skills, you will be ready to advance your career in data.

    • What is the different between the Python and the R track?

      We offer two tracks to this program, one teaching Python and one teaching R. These are both popular among data scientists. You can enroll in one or the other, not both.

      Both tracks cover the same fundamental concepts, but use a different programming language. The SQL, command line, and Git curriculum is the same in both tracks. This includes the first and third projects, which are the same between the two tracks.

      The programming course and project are different between the two tracks. One course relies on Python, while the other relies on R. The projects for the two courses rely on the same dataset and skills, but they differ in the approach and final deliverable. Learn more about the Programming for Data Science with Python Nanodegree program.

    • What is the School of Data Science, and how do I know which program to choose?

      Udacity’s School of Data consists of several different Nanodegree programs, each of which offers the opportunity to build data skills, and advance your career. These programs are organized around career roles like Business Analyst, Data Analyst, Data Scientist, and Data Engineer.

      The School of Data currently offers three clearly-defined career paths in Business Analytics, Data Science, and Data Engineering. Whether you are just getting started in data, are looking to augment your existing skill set with in-demand data skills, or intend to pursue advanced studies and career roles, Udacity’s School of Data has the right path for you! Visit How to Choose the Data Science Program That’s Right for You to learn more.

    Enrollment and admission
    • Do I need to apply? What are the admission criteria?

      No. This Nanodegree program accepts all applicants regardless of experience and specific background.

    • What are the prerequisites for enrollment?

      There are no prerequisites for enrolling aside from basic computer skills and English proficiency. You should feel comfortable performing basic operations on your computer like opening files and folders, opening applications, and copying and pasting.

    Tuition and term of program
    • How is this Nanodegree program structured?

      The Programming for Data Science with R Nanodegree program is comprised of content and curriculum to support three (3) projects. We estimate that students can complete the program in three (3) months, working 10 hours per week.

      Each project will be reviewed by the Udacity reviewer network. Feedback will be provided, and if you do not pass the project, you will be asked to resubmit the project until it passes.

    • How long is this Nanodegree program?

      Access to this Nanodegree program runs for the length of time specified above. If you do not graduate within that time period, you will continue learning with month-to-month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our Nanodegree programs.

    • Can I switch my start date? Can I get a refund?

      Please see the Udacity Program FAQs for policies on enrollment in our programs.

    • I have graduated from the Programming for Data Science with R Nanodegree program and I want to keep learning. Where should I go from here?

      Check out our Data Analyst Nanodegree program to take the programming skills you have learned and apply them to real world Data Analyst business problems. Working on these more complex projects will deepen your knowledge of coding and make you a more attractive candidate to be hired as an data analyst.

      You could also consider the Data Engineer Nanodegree program, which focuses on data models, data warehouses, and data pipelines.

    Software and hardware: What do I need for this program?
    • What software and versions will I need in this program?

      For this Nanodegree program, you will need a 64-bit computer and access to the Internet.

    Programming for Data Science with R

    Enroll Now