Dive into the world of Natural Language Processing (NLP) with this comprehensive 3.5-hour course. Explore fundamental concepts of machine learning, including supervised and unsupervised learning, class imbalance, and model evaluation. Learn essential NLP techniques such as text preprocessing and vectorization. Master various machine learning models like K-Nearest Neighbors, tree-based models, and regression models. Delve into advanced topics including neural networks, word vectors, recurrent neural networks, and transformers. Gain hands-on experience using Jupyter Notebooks on SageMaker. By the end of this accelerated course, acquire a solid foundation in NLP and its applications in modern machine learning.