AI and Machine Learning Basics for Non-Technical Professionals

8/19/2026 : 9am-12pm PST
8/20/2026 : 9am-12pm PST

Get the lowdown on AI and machine learning without the tech jargon in this chill, beginner-friendly meetup.

In this course, you will have an opportunity to learn how to:

• Describe Supervised and Unsupervised learning techniques and usages
• Compare AI vs ML vs DL
• Understand techniques like Classification, Clustering and Regression
• Discuss how to identify which kinds of technique to be applied for specific use case
• Understand the popular Machine offerings like Amazon Machine Learning, TensorFlow, Azure Machine Learning, Spark mlib, Python and R etc.
• Understand the relation between Data Engineering and Data Science
• Understand the Data Science process
• Discuss Machine Learning use cases in different domains
• Identify when to use or not use Machine Learning
• Define how to form a ML team for success
• Understand usage of tools through a ML Demo and hands-on labs.

Topic Outline:

• Course Introduction
• History and background of AI and ML
• Compare AI vs ML vs DL
• Describe Supervised and Unsupervised learning techniques and usages
• Machine Learning patterns

- Classification
- Clustering
- Regression

• Gartner Hype Cycle for Emerging Technologies
• Machine Learning offerings in Industry
• Discuss Machine Learning use cases in different domains
• Understand the Data Science process to apply to ML use cases
• Understand the relation between Data Engineering and Data Science
• Identify the different roles needed for successful ML project
• Hands-on: Create account for Microsoft Azure Machine Learning Studio
• Demo: ML using Azure ML studio
• Demo: ML using Scikit-learn
• References and Next steps