Design and Build Big Data Systems
Next start date
October 4, 2017
Big data is hot — and so are data engineers, the professionals who have the knowledge and skills to tame it. Organizations have a growing need for specialists who know how to design and build platforms that can handle the gigantic amount of data available today.
In this three-course certificate program, we’ll explore distributed computing and the practical tools used to store and process data before it can be analyzed. You’ll work with typical data stacks and gain experience with the kinds of data flow situations commonly used to inform key business decisions. Complete this program and engineer your career in the world of big data technologies.
▸ Related Article: Hot Jobs: Data Scientist
Professionals with programming experience who work with large data sets.
If you're not a native English speaker, you’ll need to have at least basic English language skills to enroll. To learn more, see English Language Proficiency Requirements.
International students are welcome to apply to an online offering of this program, which doesn’t require a visa. To enroll in a classroom offering, you must have a visa that permits study in the United States. This program does not enable students to obtain or maintain F-1 visa status. For more information, see Admission Requirements for International Students.
You must have access to a computer with the ability to run a virtual machine. Classroom students must bring laptops. A high-speed Internet connection is recommended.
You earn the certificate by successfully completing all required courses. For more information, see Completing Your Program.
Instructor David Patton of the Certificate in Big Data Technologies discusses the program and the high demand for professionals with these kinds of skills and knowledge.
You’ll use industry-standard data tools such as Hadoop, Hive and Spark.
Complete the courses listed below to earn the certificate. You may be able to take individual courses without enrolling in the certificate program; check the course pages for details.
Introduction to Data Engineering
Building the Data Pipeline
Emerging Technologies in Big Data
Certificate in Big Data Technologies
Approved by the UW Department of Computer Science & Engineering.
View this program's advisory board.
Each of our programs uses an advisory board to review content, guide design and recommend updates to ensure the program remains current as the field of study evolves. By tapping the minds of the top thinkers, doers and leaders in the field, we offer a transformational learning experience. The following individuals serve as the advisory board for this program.
Saurabh Agrawal, Senior Business Intelligence Consultant, Plaster Group
Naomi Bogenschutz, Program Manager, UW Professional & Continuing Education
Rovy Branon, Vice Provost, University of Washington Continuum College
Lyman Do, Distinguished Architect, HERE, a Nokia Company
Rob Jasper,Chief Scientist, Analysis in Motion, Pacific Northwest National Laboratory
Denny Lee, Technology Evangelist, Databricks
Dev Nambi, Data Scientist, University of Washington
David Patton, Solutions Engineer, Hortonworks
Vikas Ranjan, Principal Architect, Engineering Intelligence & Analytics, T-Mobile
Darwin Schweitzer, Technical Solutions Professional, Microsoft
Don Smith, Principal Business Intelligence Engineer, Big Fish Games
Mark Staveley, Director of Product Management, Cray Inc.
Download the application form (PDF)
Apply online, or submit an application packet that includes:
We’re currently accepting applications and will be reviewing them in the order they’re received. We’ll accept applications until the program closes.
We’ll contact you within two weeks of receiving your application materials to let you know if you’ve been accepted to the program.
If you’re accepted, we’ll send you details about your first-term course, including information on paying your course fee. Your course fee is due four weeks before the first class.
With the exception of the one-time application fee, certificate program fees are charged on a quarterly basis. Payment is due when you register.
Course fees do not include any costs for class materials such as textbooks and software.
Drops, Withdrawals & Refunds
Attend class in person and engage face to face with your classmates and instructors as part of a highly interactive curriculum. Assignments and other course materials are delivered through Canvas, a web-based learning management system that also serves as a communications hub. You must attend at least 60 percent of your class sessions in person. You may view the remainder online, either as recorded sessions or in real time (limit of two live-streamed sessions per quarter).
Courses are streamed online in real time from the classroom. You interact with your instructors and fellow students via chat, using Adobe Connect web conferencing software. Assignments and other course materials are delivered through Canvas, a web-based learning management system that also serves as a communications hub.For added flexibility, each quarter you may view recordings of up to 40 percent of your class sessions instead of attending in real time. You also can attend the classroom sessions in person if space is available.
Our special blended programs combine the convenience of online study with the vibrancy of in-person classes for a unique learning experience.
Not available for this program
Technical Architect, Cray
Lead, Partner Solution Engineering Team, Hortonworks
Principal Development Manager, Microsoft
If you’re thinking about heading back to school, you’re probably also wondering how you’ll pay for it. To help you figure that out, we’ve put together a list of ways to help fund your education.
Big data keeps getting bigger. So does the demand for skilled professionals who can make sense of it all. Read on to learn more about data scientists and what it takes to do this hot job.
Examine different aspects of data modeling and database design, and develop the conceptual knowledge and skills to create a midsize data warehouse.
Explore and evaluate the different cloud solutions offered by Amazon, Google and Microsoft, and learn how to design, implement and manage databases using the cloud.
Learn how to apply cutting-edge tools and techniques to extract meaning from data sets ranging in size from gigabytes to petabytes.
Study the probability concepts and statistical methods at the core of machine learning algorithms and explore ways to apply these techniques to address business needs and real-world challenges.
Acquire the skills needed to create resilient, elastically scalable, responsive and distributed web applications for big-data environments.
Acquire the skills to perform sophisticated data analysis and modeling, data mining and big data management using powerful statistical tools and R programming.
Gain the deep technical knowledge and interdisciplinary skills needed to turn massive data sets into insights organizations can use.
Discover how to use scientific computing tools and technologies to help solve complex problems in the physical, biological and engineering sciences.