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.

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1 个月

建议 13 小时/周

英语(English)

字幕:英语(English)

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1 个月

建议 13 小时/周

英语(English)

字幕:英语(English)

专项课程的运作方式

加入课程

Coursera 专项课程是帮助您掌握一门技能的一系列课程。若要开始学习,请直接注册专项课程,或预览专项课程并选择您要首先开始学习的课程。当您订阅专项课程的部分课程时,您将自动订阅整个专项课程。您可以只完成一门课程,您可以随时暂停学习或结束订阅。访问您的学生面板,跟踪您的课程注册情况和进度。

实践项目

每个专项课程都包括实践项目。您需要成功完成这个(些)项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程,则需要在开始之前完成其他所有课程。

获得证书

在结束每门课程并完成实践项目之后,您会获得一个证书,您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

how it works

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
22 个评分
4 条评论
课程2

课程 2

AI Workflow: Data Analysis and Hypothesis Testing

4.8
15 个评分
课程3

课程 3

AI Workflow: Feature Engineering and Bias Detection

4.6
11 个评分
课程4

课程 4

AI Workflow: Machine Learning, Visual Recognition and NLP

4.6
14 个评分
1 条评论

提供方

IBM 徽标

IBM

审阅

来自IBM AI ENTERPRISE WORKFLOW的热门评论

常见问题

  • 可以!点击您感兴趣的课程卡开始注册即可。注册并完成课程后,您可以获得可共享的证书,或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分,系统会自动为您订阅完整的专项课程。访问您的学生面板,跟踪您的进度。

  • 此课程完全在线学习,无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

  • The entire specialization will require 35-40 hours of study.  Each of the 6 courses requires 4 to 9 hours of study each.

  • It is assumed you have a solid understanding of the following topics prior to starting this course: Fundamental understanding of Linear Algebra; Understanding of sampling, probability theory, and probability distributions; Knowledge of descriptive and inferential statistical concepts; General understanding of machine learning techniques and best practices; Practiced understanding of Python and the packages commonly used in data science: NumPy, Pandas, matplotlib, scikit-learn; Familiarity with IBM Watson Studio; Familiarity with the design thinking process. If you are unsure, Course 1 includes a Readiness Exam you can take to see if you are prepared.

  • You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones.  

  • Sorry, you will not.

  • By the end of this specialization you will be able to:

    1. Build an end to end AI solution. 

    2. Leverage Design Thinking as a framework to work through the translation of business goals into AI technical implementations.

    3. Bring together different capabilities such as Machine Learning, and specialized AI use cases.

    4. Leverage Python as the tool of choice for building AI models, while integrating IBM technologies to facilitate enterprise tasks such as cross-collaboration for the creation of machine learning models, employing out-of-the-box trained models for natural language processing and visual recognition, and deploying models to production.  

  • This specialization targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises. If you are an aspiring Data Scientist, this specialization is NOT for you as you need real world expertise to benefit from the content of these courses.

  • 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. Some of the exercises in this specialization 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.

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