Natural Language Processing Basics Professional Certificate

Natural Language Processing Basics teaches you how to turn text into data and build systems that classify, search, summarise and generate language. From SMS messages and survey responses to news articles and social media, most of the world’s information is text, and NLP is how organisations make sense of it at scale.

You will start with the foundations: cleaning and tokenising text, regular expressions, part-of-speech tagging and named entity recognition with NLTK and spaCy. You will represent text with bag-of-words, TF-IDF and word embeddings, build sentiment and topic classifiers with scikit-learn, discover themes with topic modelling, and then move to modern transformer models with the Hugging Face library for classification, question answering, summarisation and generation.

Throughout the course we pay special attention to African languages, code-switching (mixing languages in one message) and the communities building NLP resources for them, as well as the responsible use of language technology. The capstone asks you to build a classifier that routes citizen SMS feedback to the right government department.

This course is for learners with basic Python and some machine learning experience; our Machine Learning Fundamentals course is the ideal preparation. How the course works: six modules, 23 lessons with more than 30 videos from educators including Hugging Face, IBM, CrashCourse and StatQuest, hands-on Colab notebooks, a quiz after every module, a capstone project and a final certification examination. Most learners finish in 8 to 10 weeks at 4 hours per week.