About this Course

최근 조회 7,154

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

다음 전문 분야의 3개 강좌 중 2번째 강좌:

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 16시간 필요

권장: 6 hours/week...

영어

자막: 영어

배울 내용

  • 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.

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

다음 전문 분야의 3개 강좌 중 2번째 강좌:

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 16시간 필요

권장: 6 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1

1

완료하는 데 10시간 필요

Project Planning and Staffing

완료하는 데 10시간 필요
12개 동영상 (총 112분), 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
Access to Course Resources10m
A Note from the Instructor5m
1개 연습문제
Module 1 Quiz10m
2

2

완료하는 데 2시간 필요

Sensors and File Systems

완료하는 데 2시간 필요
16개 동영상 (총 103분)
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
Module 2 Quiz18m
3

3

완료하는 데 3시간 필요

Machine Learning

완료하는 데 3시간 필요
22개 동영상 (총 132분)
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 Learning, 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
1개 연습문제
Module 3 Quiz22m
4

4

완료하는 데 2시간 필요

Big Data Analytics

완료하는 데 2시간 필요
19개 동영상 (총 119분)
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
1개 연습문제
Module 4 Quiz26m

검토

PROJECT PLANNING AND MACHINE LEARNING의 최상위 리뷰
모든 리뷰 보기

제공자:

콜로라도 대학교 볼더 캠퍼스 로고

콜로라도 대학교 볼더 캠퍼스

석사 학위 취득 시작

This 강좌 is part of the 100% online Master of Science in Electrical Engineering from 콜로라도 대학교 볼더 캠퍼스. If you are admitted to the full program, your courses count towards your degree learning.

Developing Industrial Internet of Things 전문 분야 정보

The courses in this specialization can also be taken for academic credit as ECEA 5385-5387, part of CU Boulder’s Master of Science in Electrical Engineering degree. Enroll here. 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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