課程信息

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第 1 門課程(共 6 門)

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中級

完成時間大約為6 小時

英語(English)

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您將獲得的技能

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

可分享的證書

完成後獲得證書

100% 在線

立即開始,按照自己的計劃學習。

第 1 門課程(共 6 門)

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為6 小時

英語(English)

字幕:英語(English)

提供方

IBM 徽標

IBM

教學大綱 - 您將從這門課程中學到什麼

1

1

完成時間為 2 小時

IBM AI Enterprise Workflow Introduction

完成時間為 2 小時
3 個視頻 (總計 12 分鐘), 13 個閱讀材料, 3 個測驗
3 個視頻
IBM Watson Studio - Create a project5分鐘
Workflow Overview3分鐘
13 個閱讀材料
About this course3分鐘
Target Audience2分鐘
Required skills2分鐘
An introduction to IBM Watson Studio and IBM Design Thinking12分鐘
Overview of IBM Watson Studio2分鐘
Am I ready?1分鐘
Am I ready to take this Specialization?3分鐘
Readiness Quiz Review12分鐘
Advantages and disadvantages of process models2分鐘
Data Science Process Models2分鐘
The design thinking process2分鐘
Data science workflow combined with design thinking13分鐘
Process Models, Design Thinking, and Introduction: Summary/Review3分鐘
3 個練習
Readiness Quiz45分鐘
Process Models & Design Thinking: Check for Understanding2分鐘
Process Models, Design Thinking, and Introduction: End of Module Quiz10分鐘
完成時間為 1 小時

Data Collection

完成時間為 1 小時
5 個視頻 (總計 17 分鐘), 5 個閱讀材料, 4 個測驗
5 個視頻
Introduction to Business Opportunities2分鐘
Introduction to Scientific Thinking for Business2分鐘
Introduction to Gathering Data2分鐘
AI Workflow: Gathering data6分鐘
5 個閱讀材料
Data Collection Objectives2分鐘
Identifying the business opportunity: Through the eyes of our Working Example5分鐘
Scientific Thinking for Business10分鐘
Gathering Data12分鐘
Data Collection: Summary/Review3分鐘
4 個練習
Business Opportunities: Check for Understanding4分鐘
Scientific Thinking for Business: Check for Understanding2分鐘
Gathering Data: Check for Understanding2分鐘
Data Collection: End of Module Quiz5分鐘
2

2

完成時間為 3 小時

Data Ingestion

完成時間為 3 小時
5 個視頻 (總計 47 分鐘), 15 個閱讀材料, 2 個測驗
5 個視頻
AI Workflow: Data ingestion6分鐘
AI Workflow: Sparse matrices for data pipeline development10分鐘
Using Watson Studio to complete the case study23分鐘
Case Study2分鐘
15 個閱讀材料
Data Engineering3分鐘
Limitations of Extract, Transform, Load (ETL)3分鐘
Data ingestion in the modern enterprise1分鐘
Enterprise data stores for data ingestion3分鐘
Why we need a data ingestion process2分鐘
Data ingestion and automation3分鐘
Sparse matrices are used early in data ingestion development5分鐘
Getting started Watson Studio3分鐘
Case Study Introduction2分鐘
Getting Started3分鐘
Data Sources2分鐘
PART 1: Gathering the data10分鐘
PART 2: Checks for quality assurance (Includes Assessment)10分鐘
PART 3: Automating the process (Includes Assessment)10分鐘
Data Ingestion: Summary/Review3分鐘
2 個練習
Ingesting Data: Check for Understanding3分鐘
Data Ingestion: End of Module Quiz

關於 IBM AI Enterprise Workflow 專項課程

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

常見問題

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  • 是的,Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请,申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤,包括毕业项目。了解更多

  • 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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