关于此 专项课程

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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.
可分享的证书
完成后获得证书
100% 在线课程
立即开始,按照自己的计划学习。
灵活的计划
设置并保持灵活的截止日期。
高级
完成时间大约为4 个月
建议 5 小时/周
英语(English)
可分享的证书
完成后获得证书
100% 在线课程
立即开始,按照自己的计划学习。
灵活的计划
设置并保持灵活的截止日期。
高级
完成时间大约为4 个月
建议 5 小时/周
英语(English)

此专项课程包含 6 门课程

课程1

课程 1

AI Workflow: Business Priorities and Data Ingestion

4.2
95 个评分
24 条评论
课程2

课程 2

AI Workflow: Data Analysis and Hypothesis Testing

4.2
65 个评分
11 条评论
课程3

课程 3

AI Workflow: Feature Engineering and Bias Detection

4.5
40 个评分
7 条评论
课程4

课程 4

AI Workflow: Machine Learning, Visual Recognition and NLP

4.5
43 个评分
9 条评论

提供方

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IBM

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