Study 10 hrs/week and complete in 6 mo.
Classroom is open.
Based on US job data
This program is comprised of two Terms. Depending on your existing skills and experience, you'll begin the program in either Term 1 or Term 2. To enter at Term 2, you must have:
Otherwise, you'll begin in Term 1. All students must successfully complete Term 2 to graduate.
Term 1: Data Analysis with Python and SQL
Understanding of Descriptive Statistics
Basic Data Skills
Term 2: Advanced Data Analysis
Experience programming in Python
Understanding of inferential statistics and probability and their applications
In this program, you’ll master the skills you need to establish a successful data science career. Our curriculum was developed with leading industry partners to ensure students master the most cutting-edge skills. Demand for qualified employees with advanced data skills has never been higher, and graduates will emerge fully job-ready.
Get started learning data science 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 the support of expert reviewers whose detailed feedback will ensure you master all the right skills.
Draw inspiration and knowledge from your student community and stay on track with the support of mentors directly in the classroom when you need guidance on specific challenges or projects.
Receive personalized feedback from experts to help you perfect your resume, refine your LinkedIn profile, and prepare for a data analyst interview.
Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
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.
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.
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.
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.
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 of the best to Udacity students.
Chris is a Full Stack Software Engineer at Udacity. He brings his experience of teaching high school mathematics to online learning.
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.
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You should be familiar with descriptive statistics and have some experience working with data in spreadsheets or SQL. See detailed requirements.
Learn Python programming fundamentals such as data types and structures, variables, loops, and functions.Explore US Bikeshare Data
Learn the data analysis process of questioning, wrangling, exploring, analyzing, and communicating data. Learn how to work with data in Python using libraries like NumPy and Pandas.Investigate a Dataset
Learn how to apply inferential statistics and probability to important, real-world scenarios, such as analyzing A/B tests and building supervised learning models.Analyze Experiment Results
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You should have experience analyzing data using Python, as well as a solid understanding of inferential statistics and its applications. See detailed requirements.
Learn to explore data at multiple levels using appropriate visualizations, acquire statistical knowledge for summarizing data, and develop intuition around a data set.Explore and Summarize Data
Learn to apply sound design and data visualization principles to the data analysis process. Learn how to use analysis and visualizations to tell a story with data.Create a Tableau Story
You should enroll in the program because you'll master the skills you need to establish a successful data science career. You'll learn to analyze data and communicate insights using powerful tools like Python, R, SQL, and Tableau. And having these skills will qualify you for a role as a data analyst. Demand for qualified employees with advanced data skills has never been higher, as data analytics quickly becomes a top priority for organizations. Our curriculum was developed with leading industry partners to ensure students master the most cutting-edge skills, and graduates will emerge fully job-ready. This is the perfect program for anyone who wants to become a data analyst or advance their career in data.
During your first week you will use local and global weather data to compare temperature trends where you live to global temperature trends.
You will use Python to perform steps of the data analysis process on bikeshare trip data collected from three US cities. You will write code to clean the data, compute descriptive statistics, and create basic visualizations of the distribution of data.
Use descriptive statistics and a statistical test to analyze the Stroop effect, a classic result of experimental psychology. Give your readers a good intuition for the data and use statistical inference to draw a conclusion based on the results.
Choose one of Udacity's curated datasets and investigate it using NumPy and Pandas. Go through the entire data analysis process, starting by posing a question and finishing by sharing your findings.
You will be provided a dataset reflecting data collected from an experiment. Use statistical techniques to answer questions about the data and report your conclusions and recommendations in a report.
Real-world data rarely comes clean. Using Python, you'll gather data from a variety of sources, assess its quality and tidiness, then clean it. You'll document your wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations using Python and SQL.
Use R and apply exploratory data analysis techniques to explore relationships in one variable to multiple variables and to explore a selected data set for distributions, outliers, and anomalies.
Create a data visualization from a data set that tells a story or highlights trends or patterns in the data. Use Tableau to create the visualization. Your work should be a reflection of the theory and practice of data visualization, such as visual encodings, design principles, and effective communication.
You will use R and apply exploratory data analysis techniques to explore relationships in one variable to multiple variables and to explore a selected data set for distributions, outliers, and anomalies.
In this project, you will look at your LinkedIn profile through the lens of a recruiter or hiring manager, focusing on how your experience, education, and interests represent you as a potential candidate for a company or collaborator on a project.
Make design decisions for an A/B test, including which metrics to measure and how long the test should be run. Analyze the results of an A/B test that was run by Udacity and recommend whether or not to launch the change.
In this project, you will create a cover letter that portrays your soft and hard skills, and most importantly your passion for the job. We highly recommend you write a unique cover letter targeted to a job posting you find online. We recommend all students create a cover letter as practice. You will learn how to showcase your skills and connect them with job requirements.
You will use descriptive statistics and a statistical test to analyze the Stroop effect, a classic result of experimental psychology. Give your readers a good intuition for the data and use statistical inference to draw a conclusion based on the results.
Choose any area of the world in https://www.openstreetmap.org and use data munging techniques, such as assessing the quality of the data for validity, accuracy, completeness, consistency and uniformity, to clean the OpenStreetMap data for a part of the world that you care about. Choose to learn SQL or MongoDB and apply your chosen schema to the project.
Play detective and put your machine learning skills to use by building an algorithm to identify Enron Employees who may have committed fraud based on the public Enron financial and email dataset.
You will choose one of Udacity's curated datasets and investigate it using NumPy and Pandas. Go through the entire data analysis process, starting by posing a question and finishing by sharing your findings.
In this project, you will update your resume according to the conventions that recruiters expect and get tips on how to best represent yourself to pass the "6 second screen". You will also make sure that your resume is appropriately targeted for the job you’re applying for. We recommend all students update their resumes to show off their newly acquired skills regardless of whether you are looking for a new job soon.
For this project, you will be given five technical interviewing questions on a variety of topics discussed in the technical interviewing course. You should write up a clean and efficient answer in Python, as well as a text explanation of the efficiency of your code and your design choices. A qualified reviewer will look over your answer and give you feedback on anything that might be awesome or lacking—is your solution the most efficient one possible? Are you doing a good job of explaining your thoughts? Is your code elegant and easy to read?
In this project, you will look at your Udacity Professional Profile through the lens of a Udacity hiring partner recruiter.
An opportunity to get started with data analysis and receive some quick feedback about your progress. Set up iPython notebook and commonly used data analysis libraries on your own computer. Use them to dig into the results of an experiment testing the optimal length of chopsticks and present your findings.
You will create a data visualization from a data set that tells a story or highlights trends or patterns in the data. Use Tableau to create the visualization. Your work should be a reflection of the theory and practice of data visualization, such as visual encodings, design principles, and effective communication.
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