Mark J Grover
This is the first course of a six part specialization. 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. This first course in the IBM AI Enterprise Workflow Certification specialization introduces you to the scope of the specialization and prerequisites. Specifically, the courses in this specialization are meant for practicing data scientists who are knowledgeable about probability, statistics, linear algebra, and Python tooling for data science and machine learning. A hypothetical streaming media company will be introduced as your new client. You will be introduced to the concept of design thinking, IBMs framework for organizing large enterprise AI projects. You will also be introduced to the basics of scientific thinking, because the quality that distinguishes a seasoned data scientist from a beginner is creative, scientific thinking. Finally you will start your work for the hypothetical media company by understanding the data they have, and by building a data ingestion pipeline using Python and Jupyter notebooks. By the end of this course you should be able to: 1. Know the advantages of carrying out data science using a structured process 2. Describe …
Instructor Details
Courses : 6
Specification: AI Workflow: Business Priorities and Data Ingestion
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3 reviews for AI Workflow: Business Priorities and Data Ingestion
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 9 hours |
| Year | 2020 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
FREE
Luis L –
Basic introduction to data ingestion pipeline.
Yifan Z –
For all of these courses, no data source has been provided 100%. All of them have an issue and can not be used for the case study. Also for the second module, even no solution has been provided in the case study solution notebook. To be honest, the lectures didn’t provide us enough material to deal with the course and I totally learn nothing from this course. It just wastes our time.
Don W –
The course goes over practical considerations relevant to applying data science in the real world, but the final case study focuses more on data ingestion. It would have been nice if there was some component dedicated to practicing the ’empathize’ stage and gaining business problem awareness.