Transformers for Natural Language Processing

The demand for language understanding is on the rise in many fields, such as media, social media, and research papers. Vast amounts of data need to be processed for research, documents need to be translated and summarized for every area of the economy, and social media posts need to be scanned for ethical and legal reasons, among hundreds of other AI tasks whose use is ever-expanding.

This course will cover everything from developing code to prompt design, a new programming skill that controls the behavior of a transformer model. Each chapter will go through the key aspects of language understanding in Python, PyTorch, and TensorFlow.

This course will discuss the architecture of the original transformer, Google BERT, OpenAI GPT-3, T5, and several other models. We will also fine-tune transformers, train models from scratch, and learn to use powerful APIs. We’ll work with large datasets from Facebook, Google, Microsoft, and other big tech corporations.

1. Ability to work with Python, PyTorch, and TensorFlow
2. Ability to explore and implement transformers, as well as key AI language understanding neural network models
3. Ability to learn the new skills required to become an Industry 4.0 AI Specialist
4. Proficiency in Python deep learning and the necessary tools needed to effectively enhance language understanding
5. Ability to create a transformer-based recommendation system