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Foundations of AI and Autonomous Systems

Welcome!

Introduction to AI in Autonomous Systems

Key Parts of Autonomous Systems

🎮 Crossword: AI Terminology

Decision Making and Challenges

How AI Makes Decisions

Analyzing Challenges in Automation

How We Study Autonomous Systems

Trust, Society, and the Future

Public Trust in Machines

Why This Technology Matters

The Future of Autonomous AI

Course Summary and Findings

Quiz

Quiz: Understanding AI Basics

Quiz: System Components

Quiz: Decision Making

Quiz: Challenges and Opportunities

Quiz: Research Methods

Quiz: Public Trust Factors

Quiz: Social Significance

Quiz: Future Trends

Quiz: Key Findings

Quiz: Final Knowledge Check

Sources

$ (USD)

AI in Autonomous Systems: Foundations, Challenges, and Public Trust is a practical, insight-rich course that demystifies how autonomous machines perceive the world, make decisions, and earn public confidence. Designed for curious professionals and students, the program walks you through core AI concepts, the key components that power autonomy (from sensors to processors), and the real-world hurdles that make safety and reliability so difficult. You will explore how AI systems analyze data in complex environments, why humans and machines may react differently to the same scenario, and how researchers validate performance through rigorous methods and data collection. Beyond the technology, the course examines public trust—what builds it, what breaks it, and how transparent design, measurable safety, and thoughtful governance can accelerate adoption. Through structured modules, visual references, and gamified activities, you will connect technical foundations with ethical, social, and policy perspectives. By the end, you’ll be able to explain how modern autonomous systems work, evaluate their limitations, interpret risk and performance claims, and discuss the opportunities for safer transportation and more accessible services. You will also look ahead to future trends, from scaling autonomy to human-AI teaming, and form an evidence-based view on the readiness of autonomous systems for the real world.

AI in Autonomous Systems: Foundations, Challenges, and Public Trust

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            <p>Imagine a world where your car knows exactly where to go without you ever touching the steering wheel, or where delivery robots navigate busy sidewalks all on their own. This is the reality of autonomous systems, where Artificial Intelligence (AI) acts as the "brain" for machines. These systems are designed with one main goal: to perform complex tasks without any human help. By using sensors to "see" and processors to "think," these machines are moving from science fiction movies into our daily lives. But as we rely more on these self-operating tools, we have to ask ourselves: what does it actually mean for a machine to be in charge?</p>

<p>Building a machine that can think is only half the battle; the real challenge lies in making sure it can make safe decisions in a messy, unpredictable world. While a computer can process data faster than any person, it might struggle with a situation that a human would find simple. This course explores the technical hurdles like safety and reliability, but it also looks at the human side of the story. Would you feel safe crossing the street if you knew a computer was driving the oncoming truck? Understanding how we build public trust and how these machines will change our future is just as important as the code that runs them.</p>
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