The course “Natural Language Processing with Machine Learning” is a comprehensive program that equips students with the necessary knowledge and skills to work with text data and apply machine learning techniques to solve NLP problems. Starting with an introduction to NLP and its challenges, the course covers essential topics such as text representation and preprocessing techniques. Students learn about supervised learning algorithms for tasks like sentiment analysis and text classification, as well as unsupervised learning methods for clustering and topic modeling. The course also delves into sequence modeling using recurrent neural networks (RNNs) and explores the applications of deep learning models, including convolutional neural networks (CNNs) and transformers, in NLP tasks. Advanced topics like natural language understanding (NLU) and discourse analysis are also covered. Throughout the course, students engage in practical exercises and projects, gaining hands-on experience in developing NLP systems and analyzing textual data. By the end of the course, students are equipped with the skills to work with NLP techniques, apply machine learning algorithms to text data and tackle real-world NLP challenges.