*Artificial Intelligence (AI) Roadmap* | |-- Fundamentals | |-- Mathematics | | |-- Linear Algebra | | |-- Calculus | | |-- Probability and Statistics | | | |-- Programming | | |-- Python (Focus on Libraries like NumPy, Pandas) | | |-- Java or C++ (optional but useful) | | | |-- Algorithms and Data Structures | | |-- Graphs and Trees | | |-- Dynamic Programming | | |-- Search Algorithms (e.g., A*, Minimax) | |-- Core AI Concepts | |-- Knowledge Representation | |-- Search Methods (DFS, BFS) | |-- Constraint Satisfaction Problems | |-- Logical Reasoning | |-- Machine Learning (ML) | |-- Supervised Learning (Regression, Classification) | |-- Unsupervised Learning (Clustering, Dimensionality Reduction) | |-- Reinforcement Learning (Q-Learning, Policy Gradient Methods) | |-- Ensemble Methods (Random Forest, Gradient Boosting) | |-- Deep Learning (DL) | |-- Neural Networks | |-- Convolutional Neural Networks (CNNs) | |-- Recurrent Neural Networks (RNNs) | |-- Transformers (BERT, GPT) | |-- Frameworks (TensorFlow, PyTorch) | |-- Natural Language Processing (NLP) | |-- Text Preprocessing (Tokenization, Lemmatization) | |-- NLP Models (Word2Vec, BERT) | |-- Applications (Chatbots, Sentiment Analysis, NER) | |-- Computer Vision | |-- Image Processing | |-- Object Detection (YOLO, SSD) | |-- Image Segmentation | |-- Applications (Facial Recognition, OCR) | |-- Ethical AI | |-- Fairness and Bias | |-- Privacy and Security | |-- Explainability (SHAP, LIME) | |-- Applications of AI | |-- Healthcare (Diagnostics, Personalized Medicine) | |-- Finance (Fraud Detection, Algorithmic Trading) | |-- Retail (Recommendation Systems, Inventory Management) | |-- Autonomous Vehicles (Perception, Control Systems) | |-- AI Deployment | |-- Model Serving (Flask, FastAPI) | |-- Cloud Platforms (AWS SageMaker, Google AI) | |-- Edge AI (TensorFlow Lite, ONNX) | |-- Advanced Topics | |-- Multi-Agent Systems | |-- Generative Models (GANs, VAEs) | |-- Knowledge Graphs | |-- AI in Quantum Computing ENJOY LEARNING👍👍