MCDA 5581

This course provides an in-depth introduction to Deep Learning (DL) and Natural Language Processing (NLP), equipping students with the theoretical foundations and practical skills necessary for advanced data science applications. Topics covered include mathematics for deep learning, artificial neural networks, text pre-processing, text classifiers, text embeddings, model performance, sequence models, language models, transformers, and model interpretability. Students will gain hands-on experience in Python, working on key DL and NLP applications. The course also emphasizes critical thinking, model evaluation and criticism, and effective communication, preparing students to tackle real-world challenges in the data science job market.