AI for Product and Business Managers: Full 4-Hour Course
AI for product and business managers — five hours on how AI actually works, built for people who make decisions about it without writing any of it. There's a specific gap this fills: you use AI tools daily, you sit in meetings where models and training data get discussed, and the vocabulary moves faster than anyone explains it. This course closes that gap properly — supervised and unsupervised learning, how models are trained and evaluated, deep learning and computer vision, NLP and language models, then generative AI across text, image, video and audio, prompt engineering, and finally the parts that matter when you're deciding whether to adopt: APIs, cloud services, what deploying AI actually involves, ethics and responsible AI, and what kind of team you need. No coding, no maths background required.
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⏱️ Chapters:
00:00:00 About This Course
00:01:58 Intro Thoughts
00:03:55 Learning Objectives
00:08:20 AI Overview
00:10:30 A Brief History of AI
00:15:53 Traditional Programming vs Machine Learning
00:20:50 AI, ML, Data Science and More
00:25:01 AI Examples in the Real World
00:28:50 Machine Learning Terms
00:32:35 AI Fundamentals Summary
00:35:59 Traditional ML vs Generative AI
00:38:37 What is Supervised Learning
00:40:33 Regression vs Classification
00:43:13 Supervised Learning in the Real World
00:47:16 Unsupervised Learning
00:50:32 K-Means Clustering
00:54:06 Unsupervised Learning in the Real World
00:59:32 Reinforcement Learning
01:02:19 Machine Learning Types Summary
01:06:49 How an ML Model Gets Built: Overview
01:10:59 Data Preparation
01:20:19 Training an ML Model
01:27:33 Model Evaluation for Classification
01:32:57 Model Evaluation for Regression
01:37:45 Model Evaluation for Unsupervised Learning
01:40:20 Introduction to Deep Learning
01:45:39 Why Deep Learning?
01:48:25 Image Recognition
01:53:05 Data Labeling
01:57:44 Data Labeling for Object Detection
02:01:12 Introduction to NLP and Language Models
02:08:46 Key NLP Techniques
02:18:22 Generative AI Recap
02:21:05 How GenAI Works
02:25:53 GenAI Models
02:38:02 Prompt Engineering Introduction
02:40:44 Prompt Engineering Techniques
02:46:34 How to Improve the Answer
02:53:25 AI for Business and Daily Life
02:56:23 Data Analysis with GenAI
03:05:02 AI-Driven Data Exploration Demo
03:12:34 AI Warning
03:15:50 GenAI Text Examples
03:28:21 GenAI Text Examples for Daily Life
03:32:12 Just Ask: Getting Started
03:34:47 Image Generation
03:42:09 GenAI for Images: Use Cases
03:45:42 Video Generation
03:55:12 GenAI for Video: Use Cases
03:58:09 Audio Generation
04:00:27 GenAI for Audio: Use Cases
04:12:03 APIs: The Bridge Between AI Models and Products
04:17:56 What is the Cloud
04:23:06 Deploying AI
04:31:50 Using AI Services
04:38:27 AI Ethics
04:41:04 Responsible AI Principles
04:52:45 Building the Right Team
04:57:10 Closing Notes
No programming experience needed — just curiosity about how any of this works.
⚠️ The generative AI sections (3:34:47 onward) reflect the tools as they were when this was recorded. Image, video and audio generation move faster than anything else in AI, so specific tools and capabilities will have shifted. The fundamentals in the first three hours don't change — that's where most of the value sits.
ℹ️ This course is independent and is not affiliated with, endorsed by, or sponsored by any company or tool mentioned. For educational purposes only, and not business or investment advice.
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