Review of Machine Learning Algorithm, Introduction to Quantum Computing-state vectors, Hilbert space, quantum states, quantum entanglement and superposition, quantum gates, and quantumcircuits, Introduction of quantum computing algorithms; Quantum machine learning (QML) basics; including representing classical data on quantum systems, quantum data encoding and embedding, quantum data representation and quantum feature maps.; Quantum Algorithms for Machine Learning; Quantum Classifiers, Quantum Kernel Methods, and Quantum Clustering.Quantum Variational Circuits, QuantumNeural Networks (QNNs), Quantum Convolutional Neural Networks (QCNNs), Quantum Federated Learning (QFL), Quantum Reinforcement Learning (QFL), Quantum Multimodal Learning. Applications and future research directions-Applications of QML in natural language processing, computer vision, healthcare, drug design, transportation, and intrusion detection.