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Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | CMU School of Computer Science, Pittsburgh |
The Syllabus
- Learn the definition of NLP
- Review current and future applications
- Define identifying characteristics of morphemesx
- Evaluate tools and resources related to morphological analysis
- Discover how computational language models are used for prediction, scoring, and correction
- Evaluate tools and resources for language model construction
- Evaluate the features of document topic classification and notation
- Demonstrate how to extract features beyond a single word
- Compare and contrast sequence-based neural networks
- Learn how neural network training works
- Explore the process of mapping strings of words to strings of tags
- Implement POS tagging with eight foreign languages
- Determine the ideal lexical approach to ascertain word meaning
- Predict word meanings using cosine similarities
- Evaluate reasons and motivations for using word embeddings
- Explore improvement techniques for word embeddings
- Analyze syntax and its applications to NLP
- Identify dependency parsing tools and resources for NLP tasks
- Translate first order logic (FOL) into English vocabulary
- Analyze approaches to the representation of meaning beyond FOL and description logics
Instructors
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