IBM AI Enterprise Workflow Course [Online, 4 Months]: Enroll Now!

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About the Course

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.

There are 6 Courses in this Specialization

  • AI Workflow: Business Priorities and Data Ingestion
  • AI Workflow: Data Analysis and Hypothesis Testing
  • AI Workflow: Feature Engineering and Bias Detection
  • AI Workflow: Machine Learning, Visual Recognition and NLP
  • AI Workflow: Enterprise Model Deployment
  • AI Workflow: AI in Production

Instructors

  • Mark J Grover
    Digital Content Delivery Lead
    IBM Data & AI Learning
  • Ray Lopez, Ph.D.
    Data Science Curriculum Leader
    IBM Data & Artificial Intelligence

To enroll in this course, click the link below.

IBM AI Enterprise Workflow Course

Note: NoticeBard is associated with Coursera through an affiliate programme.

Disclaimer : We try to ensure that the information we post on Noticebard.com is accurate. However, despite our best efforts, some of the content may contain errors. You can trust us, but please conduct your own checks too.

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