Data Preparation for AI Exercises (Part 1)

Question 1 of 8

Garbage data produces garbage models.

Question 2 of 8

What is Data engineering?

Methods, practices, approaches, and tasks required for deriving insights from data
All engineering and operational tasks required to make data available for analytics
Approaches for the development of machine learning models

Question 3 of 8

What percentage of AI Projects are Data Engineering?

Question 4 of 8

Roughly what percentage of data supplied is usable or relevant (before data cleansing)?

Question 5 of 8

Data is the heart of AI.

Question 6 of 8

You can only run AI projects if you have massive amounts of data.

Question 7 of 8

Retraining Pipelines should be part of the AI-Specific Needs of Data Preparation.

Question 8 of 8

Data pipelines follow a well-established standard