NLP (Natural Language Processing) Specialization

Bridge the gap between human communication and machine intelligence by building advanced AI models.

Duration

2 Days

Language

English

Delivery Mode

Online/Hybrid/Face-to-Face

Course Overview

This specialization offers an end-to-end journey into the world of Artificial Intelligence focused on human language. Participants will progress from fundamental text preprocessing to deploying sophisticated architectures like Transformers and RNNs. By blending statistical methods with modern deep learning, the course empowers learners to build systems capable of understanding sentiment, recognizing complex entities, and generating human-like summaries, ultimately preparing them to solve high-impact linguistic challenges in the modern tech landscape.

Learning Objectives

Apply essential text preprocessing techniques, including tokenization and lemmatization, to prepare raw data for analysis.
Build and evaluate statistical and neural language models to predict word sequences and understand linguistic context.
Implement sentiment analysis and text classification systems using both supervised learning and deep learning frameworks.
Develop Named Entity Recognition (NER) systems to accurately identify and categorize key information within large datasets.
Construct extractive and abstractive text summarization models to condense lengthy documents into concise insights.
Analyze complex linguistic structures through syntactic parsing and semantic analysis to improve machine understanding.

Course Outline

Day 01

Foundations of Text Processing: Mastering tokenization, stemming, and the removal of stop words for data cleaning.
Probabilistic and Neural Language Modeling: Exploring n-grams, Recurrent Neural Networks (RNNs), and the Transformer architecture.
Automated Text Classification: Utilizing TF-IDF, Bag-of-Words, and Convolutional Neural Networks (CNNs) for document labeling.
Information Extraction: Implementing rule-based and machine-learning approaches for Named Entity Recognition.
Advanced Language Generation: Developing sequence-to-sequence models for machine translation and abstractive summarization.
Intelligent Natural Language Understanding: Deep dives into syntactic parsing, discourse analysis, and semantic relationship mapping.

Certification

OrientMCT Certified

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