About this Course
4.0
6개의 평가
2개의 리뷰

학위 취득의 첫걸음을 내디뎌 보세요.

Master of Science in Electrical Engineering 학위에서 강의, 강좌 읽기 자료, 자가 맞춤 과제를 살펴보세요.

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

탄력적인 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 12시간 필요

권장: 7 hours/week...

영어

자막: 영어

학위 취득의 첫걸음을 내디뎌 보세요.

Master of Science in Electrical Engineering 학위에서 강의, 강좌 읽기 자료, 자가 맞춤 과제를 살펴보세요.

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

탄력적인 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 12시간 필요

권장: 7 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 10시간 필요

Project Planning and Staffing

In this module I share with you my experience in product planning, staffing and execution. You will perform a product tear down and build a bill of materials (BOM) for that product. ...
12 videos (Total 112 min), 2 readings, 2 quizzes
12개의 동영상
Segment 1 - Learning Outcomes, Introduction to a Design Process12m
Segment 2 - Requirements, Scope, Schedule, Resources, Heap Chart15m
Segment 3 - Roles and Responsibilities6m
Segment 4 - Process: Architecture Definition, Design Planning13m
Segment 5 - Process: Architecture Definition, Design Planning 218m
Segment 6 - Process: Develop9m
Segment 7 - Process: Verification11m
Segment 8 - Process: Manufacture2m
Segment 9 - Process: Deploy10m
Segment 10 - Process: Validation6m
Segment 11 - Temperature5m
2개의 읽기 자료
A Note from the Instructor5m
Project Planning and Machine Learning Course Slides10m
1개 연습문제
Quiz 110m
2
완료하는 데 2시간 필요

Sensors and File Systems

In this module you will learn about sensors, and in this case, a temperature sensor. You will learn how to calibrate and then validate that a temperature sensor is producing accurate results. We will study how data is stored on hard drives and solid state drives. We will take a brief look at file systems used to store large data sets....
16 videos (Total 103 min), 1 quiz
16개의 동영상
Segment 1 - Learning Outcomes, Introduction to Thermistors3m
Segment 2 - Terminology: Resolution, Precision, Accuracy, Tolerance6m
Segment 3 - Basic Sensor Circuit5m
Segment 4 - Accuracy Example2m
Segment 5 - Calculating Rtherm2m
Segment 6 - Validating Calibration5m
Segment 7 - Filtering Techniques11m
Segment 8 - Block, Object and Key-Value Storage Devices15m
Segment 9 - Filesystem Basics3m
Segment 10 - A File on a Hard Drive5m
Segment 11 - A File on a Solid State Drive8m
Segment 12 - File System: NFS4m
Segment 13 - How Big is "Big"?8m
Segment 14 - Traditional File System Bottlenecks3m
Segment 15 - Parallel Distributed File Systems: Hadoop, Lustre13m
1개 연습문제
Quiz 218m
3
완료하는 데 3시간 필요

Machine Learning

In this module we look at machine learning, what it is and how it works. We take a look at a couple supervised learning algorithms and 1 unsupervised learning algorithm. No coding is required of you. Instead I provide working source code to you so you can play around with these algorithms. I wrap up by providing some examples of how ML can be used in the IIoT space....
22 videos (Total 132 min), 1 reading, 1 quiz
22개의 동영상
Segment 1 - Learning Outcomes1m
Segment 2 - AI Backgrounder6m
Segment 3 - Machine Learning, What is it?6m
Segment 4 - Machine Learning Schools of Thought9m
Segment 5 - Get the Tools3m
Segment 6 - Categories of Machine Learning5m
Segment 7 - Supervised Learning, Linear Regression 17m
Segment 8 - Supervised Leraning, Linear Regression 29m
Segment 9 - Supervised Learning, Linear Regression 38m
Segment 10 - Supervised Learning, Linear Regression 49m
Segment 11 - Supervised Learning, Bayes Theorem4m
Segment 12 - Supervised Learning, Naive Bayes9m
Segment 13 - Supervised Learning, Support Vector Machines (SVM) Introduction55
Segment 14 - Supervised Learning, SVMs12m
Segment 15 - Unsupervised Learning, K-Means11m
Segment 16 - Reinforcement Learning46
Segment 17 - Supervised Learning, Deep Learning2m
Segment 18 - Rick Rashid, Natural Language Processing8m
Segment 19 - Deep Learning, Hearing Aid2m
Segment 20 - Machine Learning in IIoT4m
Segment 21 - Machine Learning Summary4m
1개의 읽기 자료
Source code examples and magazine articles10m
1개 연습문제
Quiz 322m
4
완료하는 데 3시간 필요

Big Data Analytics

In this module you will learn about big data and why we want to study it. You will learn about issues that can arise with a data set and the importance of properly preparing data prior to a ML exercise....
19 videos (Total 119 min), 1 reading, 1 quiz
19개의 동영상
Segment 1 - Learning Outcomes, Definition of Big Data3m
Segment 2 - Importance of Big Data, Characteristics of Big Data4m
Segment 3 - Size of Big Data4m
Segment 4 - Introduction to Predictive Analytics2m
Segment 5 - Role of Statistics and Data Mining3m
Segment 6 - Machine Learning, Generalization and Discrimination7m
Segment 7 - Frameworks, Testing and Validating5m
Segment 8 - Bias and Variance in your Data3m
Segment 9 - Out-of-sample Data and Learning Curves5m
Segment 10 - Cross Validation5m
Segment 11 - Model Complexity, Over- and Under-fitting3m
Segment 12 - Processing Your Data Prior to Machine Learning8m
Segment 13 - Good Data, Smart Data6m
Segment 14 - Visualizing Your Data1m
Segment 15 - Principal Component Analysis (PCA)2m
Segment 16 - Prognostic Health Management, Hadoop Machine Learning Library11m
Segment 17 - My Example: Predicting NFL Football Winners18m
Segment 18 - Tom Bradicich, Hewlett Packard's Viewpoint on Big Data20m
1개의 읽기 자료
Source code example10m
1개 연습문제
Quiz 426m

강사

Avatar

David Sluiter

Professor Adjunct
Electrical, Computer, and Energy Engineering

다른 사람보다 먼저 시작해 보세요.

이 강좌은(는) 콜로라도 대학교 볼더 캠퍼스의 100% 온라인 Master of Science in Electrical Engineering 중 일부입니다. 지금 바로 공개 강좌 또는 전문 분야를 시작하여 iMBA 교수진으로 구성된 강좌를 시청하고 자기 주도 과제를 완료해 보세요. 강좌를 완료할 때마다 이력서와 LinkedIn에 추가할 수 있는 수료증을 받습니다. 전체 프로그램을 신청하고 수료하면 귀하의 강좌가 학위 취득에 반영됩니다.

콜로라도 대학교 볼더 캠퍼스 정보

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....

Developing Industrial Internet of Things 전문 분야 정보

In this specialization, you will engage the vast array of technologies that can be used to build an industrial internet of things deployment. You'll encounter market sizes and opportunities, operating systems, networking concepts, many security topics, how to plan, staff and execute a project plan, sensors, file systems and how storage devices work, machine learning and big data analytics, an introduction to SystemC, techniques for debugging deeply embedded systems, promoting technical ideas within a company and learning from failures. In addition, students will learn several key business concepts important for engineers to understand, like CapEx (capital expenditure) for buying a piece of lab equipment and OpEx (operational expense) for rent, utilities and employee salaries....
Developing Industrial Internet of Things

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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