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            <h2>AI Course Modules</h2>
                <li class="active"><a href="../module/module1.html">Week 1: Introduction to AI</a></li>
                <li><a href="module2.html">Week 2: History of AI</a></li>
                <li><a href="module3.html">Week 3: Machine Learning</a></li>
                <li><a href="module4.html">Week 4: Deep Learning Fundamentals</a></li>
                <li><a href="module5.html">Week 5: Natural Language Processing</a></li>
                <li><a href="module6.html">Week 6: Computer Vision</a></li>
                <li><a href="module7.html">Week 7: Robotics and AI</a></li>
                <li><a href="module8.html">Week 8: Ethics in AI</a></li>
                <li><a href="module9.html">Week 9: AI in Industry</a></li>
                <li><a href="module10.html">Week 10: Future of AI</a></li>
                <li><a href="module11.html">Week 11: AI Tools and Libraries</a></li>
                <li><a href="module12.html">Week 12: Building AI Projects</a></li>
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            <h1>Module 1: Introduction to AI</h1>
            <h2>Lesson 1.1: What is Artificial Intelligence?</h2>
                Artificial Intelligence (AI) is a transformative field of computer science focused on creating machines capable of mimicking human cognitive functions such as learning, reasoning, problem-solving, and decision-making. This lesson explores the basic concepts, history, and evolution of AI to help you appreciate how past innovations contribute to current technologies.
            <h3>Historical Context and Origins</h3>
                The scientific discipline of artificial intelligence was formally established at a workshop at Dartmouth College in 1956. This marked the formal inception of AI as a field of research, setting the stage for the evolution of its technologies.
                <li><strong>1950s:</strong> The Turing Test and early AI programming.</li>
                <li><strong>1960s and 1970s:</strong> Early AI programs like ELIZA and the challenges of limited technology.</li>
                <li><strong>1980s:</strong> AI winter due to reduced funding and interest.</li>
                <li><strong>1990s:</strong> Resurgence with machine learning and the Internet.</li>
                <li><strong>2000s:</strong> Advancements in algorithms and the boom of big data.</li>
                <li><strong>2010s and Beyond:</strong> AI becomes integral to consumer technology and industry with advancements in real-world applications.</li>
            <h2>Lesson 1.2: Categories of AI</h2>
                This lesson discusses the two primary categories of AI: Narrow AI and General AI, examining their applications and implications.
            <h3>Narrow AI (Artificial Narrow Intelligence)</h3>
                <li><strong>Characteristics:</strong> Task-oriented, limited scope, example-based operations.</li>
                <li><strong>Applications:</strong> Voice assistants, recommendation systems, autonomous vehicles.</li>
            <h3>General AI (Artificial General Intelligence)</h3>
                <li><strong>Characteristics:</strong> Adaptive learning, understanding and reasoning, autonomy.</li>
                <li><strong>Future Applications:</strong> Complex decision-making, research and development, personalized education.</li>
                Understanding these categories helps contextualize the capabilities and limitations of AI technologies and provides insight into how AI can evolve in the coming years.
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