At 10 hrs/week
Get access to classroom immediately on enrollment
In Collaboration with
There are no prerequisites for this program, aside from basic computer skills.See detailed requirements.
Learn SQL fundamentals such as JOINs, Aggregations, and Subqueries. Learn how to use SQL to answer complex business problems.Investigate a Database
Learn Python programming fundamentals such as data structures, variables, loops, and functions. Learn to work with data using libraries like NumPy and Pandas.Explore US Bikeshare Data
Learn how to use version control and share your work with other people in the data science industry.Post your work on Github
from industry experts
Personal career coach and
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.
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.
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 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.
Command Line Instructor
Karl is a Course Developer at Udacity. 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.
I went into this course expecting to learn Python. Having finished the course, I find I have learned a lot more: • Python (in-depth), • Ndarrays, etc. using NumPy, • DataFrames, etc. using Pandas, • Working with many other NoSQL structures • A more powerful SQL language: PostgreSQL • Unix Shell commands • Git Perhaps even more importantly (and unexpectedly), I learned a bunch of really useful techniques to use in the coding world such as: • How to routinely work with other contributors using Git and GitHub, • Using a Shell terminal with Git Bash and Anaconda packages, • Using code editors: Atom and Visual Studio Code, • Using program output to feed Excel charts • Using Excel charts to make compelling Powerpoint slides, • Adding links to Google and Markdown Docs, • How to preview results in real time when writing Markdown docs, • Creating good README.md files and many other best practices The projects were well done and very effective in helping me apply the lessons learned in the course. I especially appreciated the Python project using just under a million real-life records of bikeshare usage data. After looking back and thinking about what I learned, to say that I highly recommend this course would be an understatement! Dave A
The SQL/Python/Git and Github lectures were very understandable. The project information in all parts were very understandable and most of the markers gave very good feedback/suggestions for improvement. The community was also quite active at times. Perhaps the mentors in the chatroom were slow to respond, but mostly they gave good advice to solve problems. Feel more comfortable showing off my progress in data analysis/science with the experienced gained from the projects.
This has been an experience which I have never felt. The materials and quizs are so awesome. I think youl will see the real power of this Nanodegree program if you have at least a month's experience in programming in general(which you can learn online for free). After that, The Udacity just changes your level of comprehension of programming. It deepens your knowledge as well as sharpen your coding skills making you multiple times better self of yourself!!!
The program was really good. Because of it, now i am able to run complex queries. One suggestion: it will be good if the course takes a small lesson to teach us what are the best tools (and how to use them) for turning a excel sheet (for example) into a database and for running queries on this newly created database. This would allow the students to start projects from scratch, apart from the already existing databases and tools at companies.
It is going well. The program is very demanding and well structured. My aim is to become a data scientist and I think this program has given me a solid foundation to begin with. I have not grasp all the concepts in the program totally but will be going back form time to time to have them all done completely. I am now waiting to have the result of the review from my Project submitted whilst continuing with the begining to learn Python.
I would highly recommend to have a summary of each block at the end of the block. There are blocks that I have to go through all the videos to find out that I'm already familiar with most concept. I would rather have a summary of that block just to have a reminder of the main concepts. Also, the Python block is not very well summarized. It should be improved. The SQL block is really well done, very well synthesized and clear.
The Programming for Data Science with Python 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 Python, SQL, terminal, and git with the help of experienced instructors.
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 Python, SQL, Terminal, and Git.
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 (Python, 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 Python and SQL, the main programing languages used by data scientists and analysts, is the core of this program. If you decide to take the Programming for Data Science with Python, you’ll also learn specialized data libraries for Python including Pandas and Numpy, and use Git and the Terminal to share your work and learn about version control. By learning these foundational programming skills, you will be ready to advance your career in data.
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 R Nanodegree program.
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.
No. This Nanodegree program accepts all applicants regardless of experience and specific background.
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.
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.
Please see the Udacity Program FAQs for policies on enrollment in our programs.
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.
For this Nanodegree program, you will need a 64-bit computer and access to the Internet.