Deploying Unsupervised AI/ML 
Methodologies with Python

Actionable Analytics
Artificial Intelligence (AI) and Machine learning (ML) is a mechanism where computers “learn” from data without requiring a large amount of human interaction. This process has given rise to a number of recent developments in technology such as: self-driving cars, natural language processing and improved understanding of the human genome.

Deploying Unsupervised AI/ML 
Methodologies with Python

Actionable Analytics
Artificial Intelligence (AI) and Machine learning (ML) is a mechanism where computers “learn” from data without requiring a large amount of human interaction. This process has given rise to a number of recent developments in technology such as: self-driving cars, natural language processing and improved understanding of the human genome.

prerequisites

Successful completion of

Taken within the last year

duration

One half-day
or two weekday evenings

Virtual or in-person

certification

afterskills AI/ML II
practitioner

Awarded upon completion

course description_

This extension series covers unsupervised learning including classification algorithms and workplace use cases.

After the course, participants will have an understanding of AI / ML algorithms, unsupervised learning, and common algorithms that can be applied on the fly.

agenda

Topic 1: Introduction to ML & Unsupervised Learning
Topic 2: Unsupervised Learning
Topic 3: Unsupervised Learning Use Case
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