This beginner-friendly Natural Language Processing (NLP) course is designed to introduce essential NLP and machine learning concepts in a simple and easy-to-understand way. The course walks you through the core building blocks of NLP, starting with basic text processing techniques such as tokenization, byte pair encoding (BPE), and regular expressions (Regex).

You will then explore how raw text is transformed into structured data using methods like part-of-speech (POS) tagging and n-grams. The course also covers important feature extraction techniques including Bag of Words (BoW) and TF-IDF, which are widely used in text analysis.

As you progress, you will learn about key algorithms for text classification such as Logistic Regression and Naive Bayes, along with concepts like minimum edit distance and optimization. The course also introduces more advanced ideas like semantic retrieval and visual grounding, helping you understand how modern AI systems interpret language beyond simple keyword matching.

This course is ideal for beginners in AI, data science, or machine learning who want a strong foundation in NLP. By the end, you will understand how text data is