課程信息
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第 1 門課程(共 6 門)

100% 在線

立即開始,按照自己的計劃學習。

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9 小時

建議:This course requires 4 to 5 hours of study....

英語(English)

字幕:英語(English)

您將獲得的技能

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

第 1 門課程(共 6 門)

100% 在線

立即開始,按照自己的計劃學習。

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9 小時

建議:This course requires 4 to 5 hours of study....

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 2 小時

IBM AI Enterprise Workflow Introduction

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

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
完成時間為 3 小時

Data Ingestion

5 個視頻 (總計 40 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 study16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

講師

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Mark J Grover

Digital Content Delivery Lead
IBM Data & AI Learning
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Ray Lopez, Ph.D.

Data Science Curriculum Leader
IBM Data & Artificial Intelligence

關於 IBM

IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame....

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

  • 注册以便获得证书后,您将有权访问所有视频、测验和编程作业(如果适用)。只有在您的班次开课之后,才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程,可能无法访问某些作业。

  • 您注册课程后,将有权访问专项课程中的所有课程,并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

  • 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. 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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