Learn R Programming | R Online Course | Udacity
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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.
Estimated time
3 Months
At 10 hrs/week
Enroll by
April 12, 2023
Get access to classroom immediately on enrollment
Skills acquired
Git, Control Flow in R, SQL Queries, SQL JOINs, SQL Aggregations
What you will learn
Learn to Code with R and SQL
3 months to completeLearn 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.
Introduction to SQL
Learn SQL fundamentals such as JOINs, Aggregations, and Subqueries. Learn how to use SQL to answer complex business problems.
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.
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.
Technical mentor support
Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.
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
- Technical mentor support
- Student community
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.
- Experienced Project Reviewers
- Technical Mentor Support
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.
Josh Bernhard
Data Scientist at Nerd WalletJosh 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 ModeDerek 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 UdacityJuno 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
InstructorRichard 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 InstructorBefore 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.
Top student reviews
Mawejje H.
Am very grateful for the opportunity that was awarded to me by AAL to be part of the program.
Indeed the program was designed in a professional manner and provides hands-on practical experience through quizzes embedded in the modules. With this, you can be able to practice writing your own query statements comparing it with the tutors which is a good practice for learning new concepts.
So far I have gained insights on how to generate meaningful information out of a batch of numbers (data) and this, best describes a data scientist. Am super excited to start a new chapter in my career
Anonymous
Really well thank you! the questions and project at the end are great for testing your knowledge. I just wish there was more depth in how to handle certain problems, perhaps including more written notes on top of videos explaining before heading straight into a question task. Also I found the estimate timeframe was significantly shorter than what it really took me.
Rabson T.
The program is going so well and am glad to say that it meets my needs let alone expectations ,I would like to apply the skills am acquiring here in medical field where databases are mostly used and I have learnt alot in this program on SQL where I can be able to pull out data from a database and use the data for analysis.
Akshat S.
The program is beautifully designed which provides you with key concepts, makes you practice & hence learn those key concepts and then tests your learning and analytical abilities through a Project. Also, the system of Mentors and Reviewers along with the Knowledge database is also quite helpful
Kwame A.
I struggled understanding the course content leading up to the first project. However, after going through the practice questions and checking the recommended solutions, I began to become more comfortable. As a result, the project wasn't as hard as I expected.
Safia B.
The program is going well, it is very well structured and I am happy that I have enrolled in it. I only would like to comment that the scheduled time per course does not really reflect an average learning time which could affect the completion in time.
Programming for Data Science with R
Get started today
Monthly access
Pay as you go
Enroll now¥ 42679
per month- Maximum flexibility to learn at your own pace.
- Cancel anytime.
3-Month access
Pay upfront and save an extra 14%
Enroll now¥ 108837
¥ 128037
for 3-Month access- Save an extra 14% vs. pay as you go.
- 3 months is the average time to complete this course.
- Switch to monthly price after if more time is needed.
- Cancel anytime.
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
- Technical mentor 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
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