Products don't design and build themselves. In this course, students learn how to staff, plan and execute a project to build a product. We explore sensors, which produce tremendous volumes of data, and then storage devices and file systems for storing big data. Finally, we study machine learning and big data analytics. This course can be taken for academic credit as part of CU Boulder鈥檚 Master of Science in Electrical Engineering (MS-EE) degree offered on the 糖心vlog官网观看 platform. The degree offers targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on 糖心vlog官网观看 are ideal for recent graduates or working professionals. Learn more: MS in Electrical Engineering: /degrees/msee-boulder
1 - Course Overview
Skills You'll Learn
Product Requirements, Data Analysis, Supervised Learning, Data Processing, File Systems, Product Planning, Machine Learning, Engineering Documentation, Unsupervised Learning, Requirements Analysis, Data Storage, Internet Of Things, Product Development, Machine Learning Algorithms, Big Data, Project Planning
Reviews
4.6 (131 ratings)
- 5 stars78.62%
- 4 stars13.74%
- 3 stars3.05%
- 2 stars2.29%
- 1 star2.29%
DB
Jul 7, 2020
Very well designed and delivered Course. Thank you for the opportunity. Special Thanks to Prof Dave Sluiter
AN
Jun 3, 2020
It was a good course to get a background and basic clearing while developing IIoT projects...
From the lesson
Project Planning and Staffing
In this module I share with you my experience in product planning, staffing and execution. You will learn about the importance of first defining requirements, second performing the design work first, and then lastly writing the code.
Taught By
David Sluiter
Professor Adjunct