At 10 hrs/week
Get access to classroom immediately on enrollment
You should have experience working with Python (specifically Numpy and Pandas) and SQL.See detailed requirements.
Learn the data analysis process of wrangling, exploring, analyzing, and communicating data. Work with data in Python, using libraries like NumPy and Pandas.Explore Weather TrendsInvestigate a Dataset
Learn how to apply inferential statistics and probability to real-world scenarios, such as analyzing A/B tests and building supervised learning models.Analyze Experiment Results
Learn the data wrangling process of gathering, assessing, and cleaning data. Learn to use Python to wrangle data programmatically and prepare it for analysis.Wrangle and Analyze Data
Learn to apply visualization principles to the data analysis process. Explore data visually at multiple levels to find insights and create a compelling story.Communicate Data Findings
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.
As the founder and president of Udacity, Sebastian’s mission is to democratize education. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass, and more.
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.
Data Analyst Instructor
Mike is a Content Developer with a multidisciplinary academic background, including math, statistics, physics, and psychology. Previously, he worked on Udacity's Data Analyst Nanodegree program as a support lead.
Data Analyst Instructor
Formerly a chemical engineer and data analyst, David created a personalized data science master's program using online resources. He has studied hundreds of online courses and is excited to bring the best to Udacity students.
Sam is the Product Lead for Udacity’s Data Analyst, Business Analyst, and Data Foundations programs. He’s worked as an analytics consultant on projects in several industries, and is passionate about helping others improve their data skills.
Very good program! I learned new interesting stuff! learning by doing is definitely the best way!
A very practical approach to very current technology skills that are becoming increasingly essential in our world today. Systematic, time-bound projects enhance not only our expertise on the subject but also help inculcate the self-discipline required to achieve our goals.
it covered many aspects of data analysis , really useful
It has overall reached beyond my expectations! What I liked the most and thought it was absolutely spectacular was the module Practical Statistics. Beyond that, the other modules were also great, very complete and deep, and I believe I have learned a lot and gained confidence using Python. What I suggest to improve is the project reviews, because some are very poor, only greeting you and cheering you, but not giving you any additional nor quality feedback. Thanks for this excellent and practical nanodegree!!
A really good course for a beginner to get a good basic foundation of data analysis. At times could be grilling but given proper time would be easy to make it through!
Numbers don't lie. See what difference it makes in career searches.*
Career-seeking and job-ready graduates found a new, better job within six months of graduation.
Average salary increase for graduates who found a new, better job within six months of graduation.
The Data Analyst Nanodegree program offers you the opportunity to master data skills that are in demand by top employers, such as Python and Statistics. By the end of the program you will have created a portfolio of work demonstrating your ability to solve complex data problems. After graduating, you will have the skills needed to join a large corporation or a small firm, or even go independent as a freelance data analyst.
You’ll have personalized support as you master in-demand skills that qualify you for high-value jobs in the data field. You’ll also receive career support via profile and portfolios reviews to help make sure you’re ready to establish a successful career in data, and land a job you love.
Graduates will be well prepared to fill a wide array of data related roles. These include: Data Analyst, Analytics Consultant, Product Manager, and Management Consultant.
If you're someone who wants to make data driven decisions or work with various types of data to conduct analyses, or is interested in becoming an data analyst, this program is ideal for you, because you'll learn applied statistics, data wrangling with Python, and data visualization with Matplotlib, which will enable you to work with any data set and find and showcase meaningful insights. This will qualify you for roles such as a Data Analyst and Analytics Consultant. You'll need to have some experience with python and pandas to succeed in this program, and if that's you, and you're ready to apply those skills to real world projects, then we encourage you to enroll today.
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 three main career roles: Business Analyst, Data Analyst, and Data Scientist.
The School of Data currently offers two clearly-defined career paths. These paths are differentiated by whether they focus on developing programming skills or not. 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.
In order to succeed in this program, we recommend having the following experience:
You should also be able to read and write in English.
The Data Analyst Nanodegree program is comprised of content and curriculum to support five (5) projects. We estimate that students can complete the program in four (4) months working 10 hours per week.
Each project will be reviewed by the Udacity reviewer network and platform. 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 Nanodegree program FAQs for policies on enrollment in our programs.
Check out our Data Scientist Nanodegree program to take the concepts you have learned in Data Analyst and build upon them using machine learning and neural networks. Learning these advanced concepts will not only enhance your knowledge it will make you a more attractive candidate to be hired as an analyst or data scientist.
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.
For this Nanodegree program you will need access to the Internet, and a 64 bit computer.
Additional software such as Python and its common data analysis libraries (e.g., Numpy and Pandas) will be required, but the program will guide students on how to download once the course has begun.