Study 10 hrs/week and complete in 4 mo.
Based on US job data
Successful Data Analysts have a unique set of skills, and represent important value to organizations eager to make data-powered business decisions. In this program, you’ll learn to use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions. Demand for qualified Data Analysts continues to rise, and as a graduate of this program, you will be prepared to take on these roles.
Get started learning data analytics through interactive content like quizzes, videos, and hands-on programs. Our learn-by-doing approach is the most effective way to learn data skills.
Advance quickly and successfully through the curriculum with detailed and personalized feedback from our reviewer network which will ensure you master all the right skills.
Draw inspiration and knowledge from your student community. Stay on track with the support of the mentor network directly in the classroom when you need guidance on specific challenges or projects.
You'll leave with core data analysis skills that will prepare you for a career in this field. Gain the insights necessary to proceed with confidence.
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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
Data Analyst Curriculum Lead
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.
Sebastian is the co-founder of Udacity and a professor at Stanford University. He’s a prominent figure in artificial intelligence where he’s known as the godfather of automated vehicles. Sebastian spends his time flying as president of Kitty Hawk.
Data Analyst Instructor
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
Data Analyst Instructor
As a data scientist at Looplist, Juno built neural networks to analyze and categorize product images, a recommendation system to personalize shopping experiences for each user, and tools to generate insight into 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.
The program was excellent. It exceeded my expectations. The project reviews and guidance by mentors was amazing too.
This was an extraordinary experience and I really liked most of the challenges
This was a great review of Statistics and introduction to Python (pandas, numpy, etc), R, Machine Learning and Data Visualization.
The exercises, quizzes and projects all contributed to my learning. Now I am comfortable in using various tools for data analysis and am able to incorporate it in my work.
To make it even easier to learn, you can finance your Nanodegree through Affirm.
As low as $84 per month at 0% APR.
Pay your monthly bill using a bank transfer, check, or debit card.
Analyze Data with Python and SQL
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 program is comprised of 1 (one) 3 (three)-month term with fixed start and end dates. Students must successfully complete all assigned projects by the end date for each term to graduate. The projects give you an opportunity to apply the skills you've learned in the lessons.
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 found here for policies on enrollment in our programs.
The full program consists of 1 (one) 4 (four)-month long term at a cost of USD $999.
Payment is due before the term begins.
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.
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.