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IntroductionSection 1: Understanding the Basics of AIWhat is Artificial Intelligence?Real-world Applications:Differences Between AI, Machine Learning (ML), and Deep LearningTypes of AI Models1. Supervised Learning:2. Unsupervised Learning:3. Reinforcement Learning:Key AI Concepts1. Algorithms, Data, and Models:2. Inputs (Features) and Outputs (Labels):Section 2: Choosing the Right Tools for AI DevelopmentProgramming Languages for AIPython: Best Language for AI and WhyAlternatives: R, JavaScript, and JuliaLibraries and FrameworksTensorFlow: Deep Learning ModelsKeras: Beginner-friendly Deep LearningScikit-learn: Machine Learning for BeginnersPyTorch: An Introduction for More Advanced UsersDevelopment EnvironmentsJupyter NotebooksGoogle Colab (Free Cloud Service for AI Training)Section 3: Data PreparationImportance of Data in AITypes of Data1. Structured vs. Unstructured Data2.…