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다음 전문 분야의 6개 강좌 중 5번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

고급 단계

완료하는 데 약 9시간 필요

권장: This course requires 7.5 to 9 hours of study....

영어

자막: 영어

귀하가 습득할 기술

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

다음 전문 분야의 6개 강좌 중 5번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

고급 단계

완료하는 데 약 9시간 필요

권장: This course requires 7.5 to 9 hours of study....

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 4시간 필요

Deploying Models

3개 동영상 (총 11분), 17 readings, 4 quizzes
3개의 동영상
Introduction to Spark5m
Model Management and Deployment in Watson Studio2m
17개의 읽기 자료
Data at scale: Through the eyes of our Working Example4m
Optimizing performance in Python5m
High performance computing4m
Apache Spark30m
Spark-submit4m
Docker containers: Through the eyes of our Working Example3m
On containers and Docker2m
Docker installation and setup2m
NVIDIA Docker4m
Getting started with Docker4m
Getting started with Flask4m
Putting it all together (hands-on tutorial)45m
More on containers3m
Watson Machine Learning: Through the eyes of our Working Example3m
Getting Started (hands-on)20m
Tutorial (hands-on)40m
Summary/Review10m
4개 연습문제
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
End of Module Quiz10m
2
완료하는 데 2시간 필요

Deploying Models using Spark

4개 동영상 (총 12분), 11 readings, 4 quizzes
4개의 동영상
Spark Recommendations1m
Recommenders6m
Introduction to Model Deployment Case Study2m
11개의 읽기 자료
Spark Machine Learning: Through the eyes of our Working Example4m
Spark Pipelines4m
Spark supervised learning4m
Spark unsupervised learning2m
Model4m
Spark Recommenders: Through the eyes of our Working Example4m
Recommendation systems4m
Recommendation systems in production4m
Model Deployment: Through the eyes of our Working Example3m
Getting Started (hands-on)1h
Summary/Review
4개 연습문제
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
End of Module Quiz10m

강사

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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 정보

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 전문 분야 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

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 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.

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