AI Foundations for Future Innovators: Core Concepts, Models, and Problem-Solving

Описание: This session provides a comprehensive introduction to the fundamental pillars of Artificial Intelligence (AI), designed to prepare learners for advanced topics like robotics and complex searching algorithms. The content focuses on the simulation of human intelligence in machines, enabling them to think, work, and make decisions like humans across various industries.
Key topics explored in this training include:
• The AI Hierarchy: A detailed breakdown of the relationship between Artificial Intelligence (the broadest field), Machine Learning (ML) (a subset focusing on learning from data), and Deep Learning (DL) (a subset using artificial neural networks to solve complex problems).
• Core Learning Models:
◦ Supervised Learning: Using labeled data to classify images or filter spam.
◦ Unsupervised Learning: Discovering hidden patterns and structures in unlabeled data, such as customer segmentation.
◦ Reinforcement Learning: A trial-and-error approach where an AI agent learns through rewards and penalties, commonly used in robotics.
• The Mechanics of AI: An overview of how AI works through data collection, processing, model training, and feedback loops to improve decision-making accuracy.
• Problem-Solving Techniques: Introduction to problem formulation (identifying initial and goal states) and search algorithms such as Breadth-First Search (BFS) and Depth-First Search (DFS) to find optimal solutions.
• Natural Language Processing (NLP): Insight into how machines understand human language through techniques like tokenization, parts of speech tagging, and name entity recognition.
• Real-World Impact and Ethics: A discussion on the advantages of AI in healthcare and finance, alongside critical challenges such as data privacy, algorithmic bias, and job displacement.
This session serves as a foundational roadmap for understanding how modern AI systems—from generative models like GPT to narrow AI applications like Google Maps—operate and evolve.

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