课程信息
5,895 次近期查看

第 1 门课程(共 6 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为9 小时

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

英语(English)

字幕:英语(English)

您将获得的技能

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

第 1 门课程(共 6 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为9 小时

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

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 2 小时

IBM AI Enterprise Workflow Introduction

3 个视频 (总计 12 分钟), 13 个阅读材料, 3 个测验
3 个视频
IBM Watson Studio - Create a project5分钟
Workflow Overview3分钟
13 个阅读材料
About this course3分钟
Target Audience2分钟
Required skills2分钟
An introduction to IBM Watson Studio and IBM Design Thinking12分钟
Overview of IBM Watson Studio2分钟
Am I ready?1分钟
Am I ready to take this Specialization?3分钟
Readiness Quiz Review12分钟
Advantages and disadvantages of process models2分钟
Data Science Process Models2分钟
The design thinking process2分钟
Data science workflow combined with design thinking13分钟
Process Models, Design Thinking, and Introduction: Summary/Review3分钟
3 个练习
Readiness Quiz45分钟
Process Models & Design Thinking: Check for Understanding2分钟
Process Models, Design Thinking, and Introduction: End of Module Quiz10分钟
完成时间为 1 小时

Data Collection

5 个视频 (总计 17 分钟), 5 个阅读材料, 4 个测验
5 个视频
Introduction to Business Opportunities2分钟
Introduction to Scientific Thinking for Business2分钟
Introduction to Gathering Data2分钟
AI Workflow: Gathering data6分钟
5 个阅读材料
Data Collection Objectives2分钟
Identifying the business opportunity: Through the eyes of our Working Example5分钟
Scientific Thinking for Business10分钟
Gathering Data12分钟
Data Collection: Summary/Review3分钟
4 个练习
Business Opportunities: Check for Understanding4分钟
Scientific Thinking for Business: Check for Understanding2分钟
Gathering Data: Check for Understanding2分钟
Data Collection: End of Module Quiz5分钟
2
完成时间为 3 小时

Data Ingestion

5 个视频 (总计 40 分钟), 15 个阅读材料, 2 个测验
5 个视频
AI Workflow: Data ingestion6分钟
AI Workflow: Sparse matrices for data pipeline development10分钟
Using Watson Studio to complete the case study16分钟
Case Study2分钟
15 个阅读材料
Data Engineering3分钟
Limitations of Extract, Transform, Load (ETL)3分钟
Data ingestion in the modern enterprise1分钟
Enterprise data stores for data ingestion3分钟
Why we need a data ingestion process2分钟
Data ingestion and automation3分钟
Sparse matrices are used early in data ingestion development5分钟
Getting started Watson Studio3分钟
Case Study Introduction2分钟
Getting Started3分钟
Data Sources2分钟
PART 1: Gathering the data10分钟
PART 2: Checks for quality assurance (Includes Assessment)10分钟
PART 3: Automating the process (Includes Assessment)10分钟
Data Ingestion: Summary/Review3分钟
2 个练习
Ingesting Data: Check for Understanding3分钟
Data Ingestion: End of Module Quiz

讲师

Avatar

Mark J Grover

Digital Content Delivery Lead
IBM Data & AI Learning
Avatar

Ray Lopez, Ph.D.

Data Science Curriculum Leader
IBM Data & Artificial Intelligence

关于 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....

关于 IBM AI Enterprise Workflow 专项课程

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

常见问题

  • 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.

还有其他问题吗?请访问 学生帮助中心