このコースについて
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次における6の1コース

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

約9時間で修了

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

英語

字幕:英語

習得するスキル

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

次における6の1コース

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

約9時間で修了

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

英語

字幕:英語

シラバス - 本コースの学習内容

1
2時間で修了

IBM AI Enterprise Workflow Introduction

3件のビデオ (合計12分), 13 readings, 3 quizzes
3件のビデオ
IBM Watson Studio - Create a project5 分
Workflow Overview3 分
13件の学習用教材
About this course3 分
Target Audience2 分
Required skills2 分
An introduction to IBM Watson Studio and IBM Design Thinking12 分
Overview of IBM Watson Studio2 分
Am I ready?1 分
Am I ready to take this Specialization?3 分
Readiness Quiz Review12 分
Advantages and disadvantages of process models2 分
Data Science Process Models2 分
The design thinking process2 分
Data science workflow combined with design thinking13 分
Process Models, Design Thinking, and Introduction: Summary/Review3 分
3の練習問題
Readiness Quiz45 分
Process Models & Design Thinking: Check for Understanding2 分
Process Models, Design Thinking, and Introduction: End of Module Quiz10 分
1時間で修了

Data Collection

5件のビデオ (合計17分), 5 readings, 4 quizzes
5件のビデオ
Introduction to Business Opportunities2 分
Introduction to Scientific Thinking for Business2 分
Introduction to Gathering Data2 分
AI Workflow: Gathering data6 分
5件の学習用教材
Data Collection Objectives2 分
Identifying the business opportunity: Through the eyes of our Working Example5 分
Scientific Thinking for Business10 分
Gathering Data12 分
Data Collection: Summary/Review3 分
4の練習問題
Business Opportunities: Check for Understanding4 分
Scientific Thinking for Business: Check for Understanding2 分
Gathering Data: Check for Understanding2 分
Data Collection: End of Module Quiz5 分
2
3時間で修了

Data Ingestion

5件のビデオ (合計40分), 15 readings, 2 quizzes
5件のビデオ
AI Workflow: Data ingestion6 分
AI Workflow: Sparse matrices for data pipeline development10 分
Using Watson Studio to complete the case study16 分
Case Study2 分
15件の学習用教材
Data Engineering3 分
Limitations of Extract, Transform, Load (ETL)3 分
Data ingestion in the modern enterprise1 分
Enterprise data stores for data ingestion3 分
Why we need a data ingestion process2 分
Data ingestion and automation3 分
Sparse matrices are used early in data ingestion development5 分
Getting started Watson Studio3 分
Case Study Introduction2 分
Getting Started3 分
Data Sources2 分
PART 1: Gathering the data10 分
PART 2: Checks for quality assurance (Includes Assessment)10 分
PART 3: Automating the process (Includes Assessment)10 分
Data Ingestion: Summary/Review3 分
2の練習問題
Ingesting Data: Check for Understanding3 分
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

IBMについて

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....

IBM AI Enterprise Workflow専門講座について

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

よくある質問

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  • コースに登録する際、専門講座のすべてのコースにアクセスできます。コースの完了時には修了証を取得できます。電子修了証が成果のページに追加され、そこから修了証を印刷したり、LinkedInのプロフィールに追加したりできます。コースの内容の閲覧のみを希望する場合は、無料でコースを聴講できます。

  • 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.

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。