關於此 專項課程

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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.
可分享的證書
完成後獲得證書
100% 在線課程
立即開始,按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
高級
完成時間大約為4 個月
建議 5 小時/週
英語(English)
可分享的證書
完成後獲得證書
100% 在線課程
立即開始,按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
高級
完成時間大約為4 個月
建議 5 小時/週
英語(English)

此專項課程包含 6 門課程

課程1

課程 1

AI Workflow: Business Priorities and Data Ingestion

4.2
95 個評分
24 條評論
課程2

課程 2

AI Workflow: Data Analysis and Hypothesis Testing

4.2
64 個評分
11 條評論
課程3

課程 3

AI Workflow: Feature Engineering and Bias Detection

4.4
38 個評分
7 條評論
課程4

課程 4

AI Workflow: Machine Learning, Visual Recognition and NLP

4.5
43 個評分
9 條評論

提供方

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IBM

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