Description:
Course Description: This course focuses on the real-world uses of natural language processing systems, including the current capabilities of natural language processing systems and how NLP can be refined and improved.
Prerequisites: None
Learning Outcome:
– Describe the capabilities of existing NLP systems
– Analyze the gap that exists between a stated scenario and the existing capabilities of NLP systems
– Test solutions by measuring improvements introduced by NLP systems
| Module |
Topic & Readings |
| Module 1 |
History of Natural Language Processing
Words vs Concepts and Explicit vs Implicit
General Domain and Specific Domain |
| Module 2 |
Shallow NNs
Contextual Embeddings
LM Capabilities |
| Module 3 |
Testing in General
Factual Correctness and Reasoning
Intro into Prompt Learning and Engineering |
| Module 4 |
Capstone Reflection Project |
Faculty: Julia Rayz