Approx. 2 months
(work at your own pace)
The Introduction to Data Science class will survey the foundational topics in data science, namely:
The class will focus on breadth and present the topics briefly instead of focusing on a single topic in depth. This will give you the opportunity to sample and apply the basic techniques of data science.
You will have an opportunity to work through a data science project end to end, from analyzing a dataset to visualizing and communicating your data analysis.
Through working on the class project, you will be exposed to and understand the skills that are needed to become a data scientist yourself.
The ideal students for this class are prepared individuals who have:
If you need to brush up on your programming, we highly recommend Introduction to Computer Science: Building a Search Engine. If you need a refresher on statistics, enroll in Statistics: The Science of Decisions. Both classes are on Udacity!
See the Technology Requirements for using Udacity
Use statistical analysis, machine learning, and MapReduce to discover interesting patterns and trends about the New York Subway.
Dave Holtz is currently a data scientist at AirBnB. Before AirBnB, he was formerly a data science engineer at Yub, the world's first online-to-offline affiliate network, and he also worked as a product manager and data scientist at TrialPay. Dave holds an M.A. in physics and astronomy from the Johns Hopkins University and a B.A. in physics from Princeton University. In addition to data science, Dave is passionate about cosmology, smart cities, music, theater, and improv comedy.
Cheng-Han worked as a program manager at Microsoft prior to Udacity, and he studied at the University of Texas at Austin and University of California at San Diego for his degrees in computer science.
Outside of work, Cheng-Han is a world traveler. He has lived in Taiwan, Shanghai, Charleston (SC), Dallas, Austin, San Diego, Seattle, and now the Bay Area. In addition to traveling, he likes to find new parks to explore, new venues to visit, and new restaurants to try.