Natural Language Processing - Fall 2025

Natural Language Processing - Fall 2025

UofU Data Science via YouTube Direct link

seq2seq (through the lens of NMT)

15 of 23

15 of 23

seq2seq (through the lens of NMT)

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Classroom Contents

Natural Language Processing - Fall 2025

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  1. 1 (Q)LoRA; Course wrap
  2. 2 Quantization & KV cache
  3. 3 DPO & Reasoning LMs
  4. 4 SFT data & RLHF
  5. 5 LLM-as-judge; Instruction finetuning / SFT
  6. 6 Summarization & Text generation evaluation
  7. 7 Answer extraction & RAG
  8. 8 QA landscape & Retrieval
  9. 9 Review & Pretraining data
  10. 10 Pretraining & finetuning
  11. 11 Transformers Part 2
  12. 12 Transformers Part 1
  13. 13 Subword tokenization
  14. 14 Attention
  15. 15 seq2seq (through the lens of NMT)
  16. 16 Language modeling
  17. 17 Word embeddings: Eval & analysis + Course preview
  18. 18 Word embeddings: word2vec skip-gram
  19. 19 Neural networks foundations: Part 2
  20. 20 Neural networks foundations: Part 1
  21. 21 Machine learning foundations: Part 2
  22. 22 Machine learning foundations: Part 1
  23. 23 Course Overview & Logistics

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