Course Notes

Week 1 Introduction to Natural Language Processing (NLP)

KeyConceptWhat is NLP?

Problems solved by using NLP

The different roles that work with NLP applications

Reading Nguyen et al. 2020

Code Python Fundamentals

Week 2 Text as Data

Text processing stages

Types of text extraction

KeyConceptTasks for text processing

Stemming versus lemmatization

Reading Regular Expressions, Text Normalization, Edit Distance

Code Getting started with Text Preprocessing

Week 3 Word Embedding

Tokenization

KeyConceptHow the machine reads text

Beyond word embeddings

Reading Understanding word embedding-based analysis
Reading Counting words by Michael Gavin

Code Word embeddings

Week 4 Sentiment Analysis

KeyConceptUnveiling the emotional essences of content

Algorithms for sentiment analysis

Sentiment analysis lexicons

Challenges of analyzing social media data

Reading Vader Paper by Hutto, C. & Gibert, E.

Code Sentiment Analysis with machine learning algorithms

Week 5 Information Extraction

Part of Speech

Name Entity recognition (NER)

KeyConceptFrom data to information

Regular Expression

Reading Named Entity Recognition from geeksforgeeks

Code Information Extraction with NLTK and spaCY

Week 6 Topic Modeling

KeyConceptNot just a topic

Topic modeling with LDA

Topic modeling with Transformers

Reading What is topic modeling from datacamp

Code Topic Modeling

Week 7 Large Language Models (LLMs)

KeyConceptLLMs, exploring the Giants’ language

Understand Transformers

Bert explained

Different types of LLMs

Reading Bert paper by Devlin et al.
Reading How Large Language Models Will Transform Science, Society, and AI

Code Explore LLMs

Week 8 Generative AI

Evolution of Machine Learning for practical use

Foundation models

KeyConceptPrompt Engineering: How to chat with AI

Application integration

Reading Generative AI: A Creative New World

Code Generative AI