This course provides a comprehensive introduction to Text Analytics using Natural Language Processing (NLP). It is designed to help participants understand the techniques and tools used to analyze, process, and derive insights from textual data. The course covers key concepts such as text preprocessing, tokenization, sentiment analysis, topic modeling, and text classification. Through hands-on exercises and real-world examples, participants will learn how to apply NLP techniques to various applications, including sentiment analysis, customer feedback analysis, and automated content generation.
Course Duration
5 Days
Who Should Attend
- Data scientists
- Data analysts
- Machine learning engineers
- Business analysts
- Anyone interested in leveraging text data for insights
Course Objectives
By the end of this course, participants will be able to:
- Understand the fundamentals of natural language processing
- Preprocess text data for analysis
- Apply various NLP techniques to extract information from text
- Build text classification and sentiment analysis models
- Utilize NLP for information retrieval and summarization
Course Outline:
Module 1: Introduction to Natural Language Processing (NLP)
- Overview of NLP
- Key components of NLP (tokenization, stemming, lemmatization, stop words)
- NLP applications (sentiment analysis, text classification, machine translation)
Module 2: Text Preprocessing
- Text cleaning and normalization
- Handling missing data
- Text representation (bag-of-words, TF-IDF)
- N-grams and language models
Module 3: Feature Engineering for Text
- Text feature extraction
- Feature selection and dimensionality reduction
- Text embedding techniques (Word2Vec, GloVe)
Module 4: Text Classification and Sentiment Analysis
- Supervised learning for text classification
- Naive Bayes, Support Vector Machines, Random Forest
- Sentiment analysis techniques
- Performance evaluation metrics
Module 5: Advanced NLP Topics
- Named Entity Recognition (NER)
- Text summarization
- Information retrieval
- Natural Language Generation
