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IBM

강의 계획 - 이 강좌에서 배울 내용

1

1

완료하는 데 2시간 필요

IBM AI Enterprise Workflow Introduction

완료하는 데 2시간 필요
3개 동영상 (총 12분), 13 개의 읽기 자료, 3 개의 테스트
3개의 동영상
IBM Watson Studio - Create a project5m
Workflow Overview3m
13개의 읽기 자료
About this course5m
Target Audience2m
Required skills2m
An introduction to IBM Watson Studio and IBM Design Thinking12m
Overview of IBM Watson Studio2m
Am I ready?1m
Am I ready to take this Specialization?3m
Readiness Quiz Review12m
Advantages and Disadvantages of Process Models2m
Data Science Process Models2m
The Design Thinking Process2m
Data Science Workflow Combined with Design Thinking13m
Process Models, Design Thinking, and Introduction: Summary/Review3m
3개 연습문제
Readiness Quiz1시간
Process Models & Design Thinking: Check for Understanding2m
Process Models, Design Thinking, and Introduction: End of Module Quiz10m
완료하는 데 1시간 필요

Data Collection

완료하는 데 1시간 필요
5개 동영상 (총 17분), 5 개의 읽기 자료, 4 개의 테스트
5개의 동영상
Introduction to Business Opportunities2m
Introduction to Scientific Thinking for Business2m
Introduction to Gathering Data2m
AI Workflow: Gathering data6m
5개의 읽기 자료
Data Collection Objectives2m
Identifying the Business Opportunity: Through the Eyes of our Working Example5m
Scientific Thinking for Business10m
Gathering Data12m
Data Collection: Summary/Review3m
4개 연습문제
Business Opportunities: Check for Understanding4m
Scientific Thinking for Business: Check for Understanding2m
Gathering Data: Check for Understanding2m
Data Collection: End of Module Quiz5m
2

2

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Data Ingestion

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5개 동영상 (총 41분), 15 개의 읽기 자료, 2 개의 테스트
5개의 동영상
AI Workflow: Data ingestion6m
AI Workflow: Sparse matrices for data pipeline development10m
Using Watson Studio to complete the case study17m
Case Study2m
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Data Engineering3m
Limitations of Extract, Transform, Load (ETL)3m
Data ingestion in the modern enterprise1m
Enterprise data stores for data ingestion3m
Why we need a data ingestion process2m
Data ingestion and automation3m
Sparse matrices are used early in data ingestion development5m
Getting started Watson Studio3m
Case Study Introduction2m
Getting Started3m
Data Sources2m
PART 1: Gathering the data10m
PART 2: Checks for quality assurance (Includes Assessment)10m
PART 3: Automating the process (Includes Assessment)10m
Data Ingestion: Summary/Review3m
2개 연습문제
Ingesting Data: Check for Understanding3m
Data Ingestion: End of Module Quiz

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AI WORKFLOW: BUSINESS PRIORITIES AND DATA INGESTION의 최상위 리뷰

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IBM AI Enterprise Workflow 특화 과정 정보

This six course specialization is designed to prepare you to take the certification examination for IBM AI Enterprise Workflow V1 Data Science Specialist. IBM AI Enterprise Workflow is a comprehensive, end-to-end process that enables data scientists to build AI solutions, starting with business priorities and working through to taking AI into production. The learning aims to elevate the skills of practicing data scientists by explicitly connecting business priorities to technical implementations, connecting machine learning to specialized AI use cases such as visual recognition and NLP, and connecting Python to IBM Cloud technologies. The videos, readings, and case studies in these courses are designed to guide you through your work as a data scientist at a hypothetical streaming media company. Throughout this specialization, the focus will be on the practice of data science in large, modern enterprises. You will be guided through the use of enterprise-class tools on the IBM Cloud, tools that you will use to create, deploy and test machine learning models. Your favorite open source tools, such a Jupyter notebooks and Python libraries will be used extensively for data preparation and building models. Models will be deployed on the IBM Cloud using IBM Watson tooling that works seamlessly with open source tools. After successfully completing this specialization, you will be ready to take the official IBM certification examination for the IBM AI Enterprise Workflow....
IBM AI Enterprise Workflow

자주 묻는 질문

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • 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.

  • 구독하는 경우, 취소해도 요금이 청구되지 않는 7일간의 무료 평가판을 이용할 수 있습니다. 해당 기간이 지난 후에는 환불이 되지 않지만, 언제든 구독을 취소할 수 있습니다. 전체 환불 정책 보기.

  • 예, Coursera에서는 수업료를 낼 수 없는 학습자를 위해 재정 지원을 제공합니다. 왼쪽에 있는 등록 버튼 아래 재정 지원 링크를 클릭하면 지원할 수 있습니다. 신청서를 작성하라는 메시지가 표시되며 승인되면 알림을 받습니다. 성취 프로젝트를 포함하여 전문 분야의 각 강좌에서 이 단계를 완료해야 합니다. 자세히 알아보기.

  • This course assumes that you are already familiar with basic data science concepts including probability and statistics, linear algebra, machine learning, and the use of Python and Jupyter. If you are unsure we do offer a Readiness Exam you can take to see if you are prepared.

  • No. The certification exam is administered by Pearson VUE and must be taken at one of their testing facilities. You may visit their site at https://home.pearsonvue.com/ for more information.

  • Please visit the Pearson VUE web site at https://home.pearsonvue.com/ for the latest information on taking the AI Enterprise Workflow certification test.

  • It is highly recommended that you have at least a basic working knowledge of design thinking and Watson Studio prior to taking this course. Please visit the IBM Skills Gateway at http://ibm.com/training/badges and "Find a Badge" related to "design thinking" or "Watson Studio". From there you will be directed to courses covering these topics.

  • No. Most of the exercises may be completed with open source tools running on your personal computer. However, the exercises are designed with an enterprise focus and are intended to be run in an enterprise environment that allows for easier sharing and collaboration. The exercises in the last two modules of the course are heavily focused on deployment and testing of machine learning models and use the IBM Watson tooling found on the IBM Cloud.

  • Yes. All IBM Cloud Data and AI services are based upon open source technologies.

  • The exercises in the course may be completed by anyone using the IBM Cloud "Lite" plan, which is free for use.

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