Advanced NLP

Advanced Level

Advanced Natural Language Processing techniques and applications for experienced ML practitioners

12 weeks
Advanced

Course Overview

  • State-of-the-art language models and their architectures
  • Advanced semantic analysis and representation learning
  • Multi-lingual and cross-lingual NLP techniques
  • Domain-specific adaptation and fine-tuning
  • NLP for complex reasoning and knowledge extraction
  • Building production-ready NLP pipelines and systems

Course Modules

Advanced Language Model Architectures

2 weeks

Topics Covered

  • Evolution of language models from BERT to modern architectures
  • Transformer variants and efficient attention mechanisms
  • Scaling laws and emergent abilities in large language models
  • Mixture of experts and sparse architectures
  • Retrieval-augmented language models

Assignments

  • Comparative analysis of modern LLM architectures
  • Implementing efficient attention mechanisms

Instructor

Dr. Neetu Sharma

Dr. Neetu Sharma

Co-founder

Ph.D in Computer Science with specialization in computational linguistics and natural language processing. Pioneer in implementing state-of-the-art NLP systems for enterprise solutions.

Prerequisites

  • Strong foundation in machine learning fundamentals
  • Experience with deep learning frameworks
  • Prior work with basic NLP tasks and models
  • Understanding of transformer architectures
  • Proficiency in Python and relevant ML/NLP libraries

What You'll Learn

  • Design and implement state-of-the-art NLP systems
  • Adapt advanced language models to specific domains
  • Build multilingual and cross-lingual NLP solutions
  • Develop systems capable of complex reasoning and knowledge extraction
  • Deploy efficient and scalable NLP systems in production
  • Evaluate and mitigate ethical concerns in advanced NLP applications

Certification

Advanced NLP Certification

Upon successful completion of all course modules and the capstone project, participants will receive a verified certification in Advanced Natural Language Processing.

Complete all module assignments and the final capstone project with a score of 80% or higher.

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