Overview

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Artificial intelligence, machine learning, deep learning, and neural networks are transforming how businesses operate, compete, and make decisions. This course explores how AI and machine learning work and how organizations across industries use tools like ChatGPT, generative AI, computer vision, and natural language processing to solve real business problems. You'll learn to differentiate supervised, semi-supervised, unsupervised, reinforcement, and deep learning, and understand how neural networks process data to power AI applications such as image recognition, speech recognition, robotics, and intelligent agents. Through real-world examples from Amazon, JPMorgan Chase, Wayfair, and other leading companies, you'll explore how AI is applied in accounting, finance, marketing, operations, human resources, and information systems. By the end of this course, you'll be able to evaluate AI and machine learning opportunities, communicate confidently with technical teams, and apply AI-informed thinking to real business decisions, regardless of your major or industry. No coding or technical background required.

Syllabus

AI Foundations: Machine Learning, Deep Learning, and Neural Networks
- Artificial intelligence and machine learning are reshaping how organizations compete, and understanding the fundamentals is now essential for professionals in every field, not just technical roles. This module introduces AI, machine learning, and neural networks: the foundational technologies powering tools like ChatGPT, recommendation engines, and predictive systems used across industries today. You'll explore the potential value and real limitations of AI, compare strong AI versus weak AI, and see how machine learning differs from traditional programming and expert systems. You'll differentiate supervised, semi-supervised, unsupervised, reinforcement, and deep learning, and examine common sources of bias in machine learning models. Finally, you'll look inside a neural network to understand how nodes, weights, and activation functions work together to power machine learning. This foundation prepares you to speak the language of AI with confidence in any professional setting.💡 Tip for Success: As you learn each type of machine learning, think of an everyday app you use, like a streaming recommendation or a spam filter, and try to identify which type of learning powers it.
AI Applications Across the Enterprise
- AI is no longer confined to the IT department. This module shows you how artificial intelligence and machine learning are already at work across every business function; from helping organizations predict customer needs to detecting fraudulent transactions. You'll explore real-world AI applications including computer vision, natural language processing, robotics, speech recognition, and intelligent agents. You'll also learn how neural networks, including CNNs, RNNs, and transformer models like GPT, power many of these technologies. You'll then see how organizations apply these tools in accounting, finance, marketing, operations, human resources, and information systems, using examples from Amazon, JPMorgan Chase, and the NFL. A guided walkthrough demonstrates how a neural network processes data, learns patterns, and improves its outputs over time. By the end of this module, you'll be able to identify AI opportunities and risks relevant to your own field. 💡Tip for Success: As you review each functional area, pay closest attention to your own field. You'll walk away with specific, ready-to-use examples for your next interview or performance review.
Course Graded Assignment
- Summative assessment for the course