This course provides practical instruction on transformer architectures such as BERT, GPT, and T5. You will learn about attention mechanisms, transfer learning, and model fine-tuning through coding exercises and case studies. By the end, you will be able to build and optimize NLP models for various applications.

Praktisches Lernprojekt

In this course, you will apply your knowledge of transformer models by building a complete NLP pipeline from start to finish. Guided by real-world case studies, you will preprocess and tokenize text data, implement and fine-tune transformer architectures such as BERT and GPT, and evaluate model performance on practical tasks like text classification and question answering. By the end of the project, you will have hands-on experience developing, deploying, and sharing robust NLP solutions using state-of-the-art transformer techniques, preparing you to tackle real-world language processing challenges with confidence.