Project Planning and Machine Learning

Name: Project Planning and Machine Learning
Brand: Coursera
SKU: 38782
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David Sluiter 8 Machine Learning Coursera

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8.7/10 (Our Score)

Product is rated as #85 in category Machine Learning

This course can also be taken for academic credit as ECEA 5386, part of CU Boulder’s Master of Science in Electrical Engineering degree. This is part 2 of the specialization. In this course students will learn : * How to staff, plan and execute a project * How to build a bill of materials for a product * How to calibrate sensors and validate sensor measurements * How hard drives and solid state drives operate * How basic file systems operate, and types of file systems used to store big data * How machine learning algorithms work – a basic introduction * Why we want to study big data and how to prepare data for machine learning algorithms CU–Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.

Instructor Details

David Sluiter

Votes: 0

Courses : 3

I joined the Department of Electrical, Computer, and Energy Engineering at the University of Colorado Boulder in the Fall of 2016 as an Adjunct Professor teaching undergraduate courses in logic design. In the Spring of 2017 I joined the graduate school and the Embedded Systems Engineering Program to create and teach a new course: Developing the Industrial Internet of Things. I earned my B.S. in Electrical and Computer Engineering at Michigan Technological University. I joined Sperry Univac designing a cache controller and then the floating point unit for the 2200 series mainframes. I then joined a small graphics company where I designed 3D graphics chips for PCs. In 1995 I moved to Colorado to open the first LSI Logic office in the state. My role was North American Field Coreware Manager leading a small team of engineers embedding MIPS microprocessors into many dozens of chips. Later I moved from management back into engineering in LSI's Consumer group where I functioned as lead hardware architect for satellite set-top box decoders. With Colorado being somewhat of a storage mecca, I joined Seagate in 2006 and developed the logic for Seagate's first self encrypting hard drives. I then moved on to become lead hardware architect for solid state enterprise drives. My most recent corporate role was Senior Systems Engineer at SEAKR Engineering where I assisted in the development of a significantly large and complex chip for satellite communications. More info can be found on LinkedIn. On the technical front, my areas of expertise include physical layout of standard cell designs, Verilog and SystemVerilog for design, logic synthesis, static timing analysis, power analysis, test insertion and automatic test pattern generation, and constrained random verification. Additional expertise includes the storage protocols SATA, SAS and PCIe/NVMe.

Specification: Project Planning and Machine Learning

Duration	16 hours
Year	2019
Level	Intermediate
Certificate	Yes
Quizzes	Yes

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Andreu C – February 8, 2019
Mas orientado a embedded systems
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Anni B – April 2, 2019
quizzes can be tougher. great course! 100% history oriented.
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