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