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.
Introduction to Data Analysis
Course
Start your data science journey right with this hands-on introduction to the discipline of data analysis. In this course you'll learn the 5 key stages of the data analysis process and apply them to real data sets using Python libraries NumPy, pandas, and Matplotlib.
Estimated time
1 month
Enroll by
June 14, 2023
Get access to classroom immediately on enrollment
Skills acquired
Data Analysis Process, Pandas, NumPy
In collaboration with
What You Will Learn
Intro to Data Analysis
1 month to completeData analysis is a rigorous discipline that can reveal illuminating insights, but a strong grasp of the fundamentals is essential to generating accurate, useful results. This hands-on course will teach you the industry-standard framework for analyzing data of any kind, and show you how to apply it using some of the most popular tools in data science.
Prerequisite knowledge
Python.
Anaconda
Learn to use Anaconda to manage packages and environments for use with Python.
Jupyter Notebooks
Learn to use this open-source web application to combine explanatory text, math equations, code and visualizations in one sharable document.
Data Analysis Process
Learn about the keys steps of the data analysis process and investigate multiple datasets using Python and Pandas.
Pandas and NumPy: Case Study
Perform the entire data analysis process on a dataset and learn to use NumPy and Pandas to wrangle, explore, analyze and visualize data.
Programming Workflow for Data Analysis
Learn about how to carry out analysis outside Jupyter notebook using IPython or the command line interface.
Course Project: Investigate a Dataset
In this project, you’ll choose one of Udacity’s curated datasets and investigate it using NumPy and pandas. You’ll complete the entire data analysis process, starting by posing a question and finishing by sharing your findings.
All Our Courses Include
Real-time support
On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.
Workspaces
Validate your understanding of concepts learned by checking the output and quality of your code in real-time.
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.
Course offerings
Class content
- Real-world projects
- Project reviews
- Project feedback from experienced reviewers
Student services
- Student community
- Real-time support
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
- Real-Time 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.
Learn with the best.
Mat Leonard
InstructorMat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
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.
Intro to Data Analysis
Get started today
Learn
The 5 stages of the data analysis process and work through them with Python libraries Pandas, NumPy, and Matplotlib.
Average Time
On average, successful students take one month to complete this program.
Benefits include
- Real-world projects from industry experts
- Real-time support
Program Details
Do I need to apply? What are the admission criteria?
No. This Course accepts all applicants regardless of experience and specific background.
What are the prerequisites for enrollment?
In order to succeed in this program, we recommend having experience working with data in Python, ideally with the NumPy and/or pandas libraries.
How is this course structured?
The Intro to Data Analysis course is comprised of content and curriculum to support one project. We estimate that students can complete the program in one month.
The 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.
How long is this course?
Access to this course runs for the length of time specified in the payment card 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 programs.
Can I switch my start date? Can I get a refund?
Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.
What software and versions will I need in this course?
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.