Study Guide

Objective

You can design a basic machine learning pipeline in a given cloud platform
You can work with centralized data management, analytics and machine learning AI deployment services
You can optimize your AI solutions by using the features of the given cloud platform
You can use your machine learning pipeline solution in practice

Content

Common cloud platforms for machine learning pipelines
The purpose of machine learning pipelines in working life
Data management and analysis features in cloud platforms
Building, maintaining and deploying cloud-based AI solutions
The process of creating and operating a functional machine learning pipeline

Qualifications

Basics of conventional machine learning methods, Basics of Python data analytics modules/libraries, Basics of Cloud-based machine learning applications (Natural language, Images)

Assessment criteria, satisfactory (1)

You can create a simple machine learning pipeline and use it in practice
You are aware of the reasons why machine learning pipelines are used in the industry
You are aware of different cloud service platforms regarding machine learning pipelines

Assessment criteria, good (3)

You can create an intermediate machine learning pipeline and use it in practice
You understand the reasons why machine learning pipelines are used in the industry
You have studied different cloud service platforms regarding machine learning pipelines

Assessment criteria, excellent (5)

You can create an advanced machine learning pipeline and use it in practice
You can effectively monitor machine learning pipelines you have created
You understand the reasons why machine learning pipelines are used in the industry
You have studied different cloud service platforms regarding machine learning pipelines
You can optimize your machine learning pipelines based on configurations and data optimizations