Lilly Tech Systems
Learn Natural Language Processing
Master the science of teaching machines to understand human language. From text preprocessing to transformers and large language models — all for free.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What is NLP? Explore the history, challenges, and real-world applications of Natural Language Processing.
2. Text Preprocessing
Tokenization, stopword removal, stemming, lemmatization, and cleaning text data for NLP pipelines.
3. Text Representation
Bag of Words, TF-IDF, Word2Vec, GloVe, and contextual embeddings like BERT and GPT.
4. NLP Tasks
Text classification, NER, POS tagging, translation, summarization, question answering, and generation.
5. Transformers & LLMs
The transformer revolution: BERT, GPT, T5, and modern large language models with fine-tuning and RAG.
6. Hugging Face
The Hugging Face ecosystem: Transformers library, Model Hub, Pipeline API, Datasets, and Trainer.
7. Best Practices
Data collection, evaluation metrics, bias handling, multilingual text, and production deployment.
What You'll Learn
By the end of this course, you will be able to:
Process Text Data
Clean, tokenize, and transform raw text into structured data ready for machine learning models.
Build NLP Pipelines
Create end-to-end NLP solutions for classification, entity recognition, summarization, and more.
Use Transformers
Leverage pretrained transformer models from Hugging Face for state-of-the-art NLP tasks.
Deploy NLP Models
Understand best practices for evaluating, optimizing, and deploying NLP models in production.