Text Analytics and Sentiment Mining using SAS Training Course and Workshop in Bangalore, Mysore, Chennai, Hyderabad, Pune, Mumbai, Delhi, Noida, Gurgaon, Kolkata

While the amount of textual data are increasing rapidly, businesses' ability to summarize, understand, and make sense of such data for making better business decisions remain challenging. No marketing or customer intelligence program can be effective today without thoroughly understanding how to analyze textual data. Emphasizing practical skills as well as providing theoretical knowledge, this Text Analytics and Sentiment Mining using SAS training course takes a comprehensive look at how to organize, manage, and mine textual data for extracting insightful information from large collections of documents and using such information for improving business operations and performance.

By attending Text Analytics and Sentiment Mining using SAS workshop, delegates will learn to:

Gain a deep understanding of tools and techniques of text analytics and sentiment mining from statistical and NLP (natural language processing) perspectives
Import text data into SAS Text Miner from different sources and different formats
Create clusters from text data to understand customer segments
Derive topics from text data to better understand customer conversation
Create rules from text data to make predictions
Combine text data with numeric data to build better models
Create statistical, rule-based, and hybrid models for understanding and predicting customer sentiments
Create statistical and rule-based models to categorize documents into a specified taxonomy

Experience with SAS and SAS Enterprise Miner is useful, but it is not mandatory. No experience with text analysis is necessary.

This Text Analytics and Sentiment Mining using SAS class is suitable for Business analysts, web analysts, BI professionals, customer intelligence professionals, data analysts, market researchers, marketing analysts, social media analysts, text analysts, and data miners.

Text Analytics and Sentiment Mining

History and roots of text analytics
SAS tools and components for text analytics
Application areas of Text Analytics

Getting Textual Data into SAS Enterprise Miner and SAS Text Miner

Introduction to SAS Enterprise Miner and SAS Text Miner
Demonstration of the Text Import node for Web crawling
Demonstration of the File Import node for reading Excel files
Demonstration of XML mapper for reading XML files

Text Parsing and Using Term by Document Matrix

Bag-Of-Words versus NLP approach in parsing
Tokenization, lemmatization, POS Tags, phrase and entity recognition
Weights and transformations used in handling term-by-document matrix
Demonstration of text parsing, text filtering, text search, and concept links

Clustering and Topic Extraction

Different types of similarity metrics and methods used in clustering
Different clustering algorithms available in SAS
SVD and LSI for clustering textual data
Differences between the the Text Cluster node and the Text Topic node
Demonstration of Text Cluster and Text Topic extraction

Predictive Modeling and Text Rule Builder

Predictive modeling essentials for text and numeric data
Demonstration of Text Rule Builder node for model building using text data
Demonstration of the Text Cluster node and the Text Topic node for model building using text data
Demonstration of model building using both numeric and textual data

Sentiment Analysis and Opinion Mining

Basics of sentiment analysis
Architecture and types of models in SAS Sentiment Analysis Studio
Demonstration of statistical and rule-based model building in SAS Sentiment Analysis Studio

Content Categorization, Concept Extraction, Wrap-up, and Takeaways

Basics of content categorization
Architecture and types of rules supported in SAS Content Categorization Studio
Demonstration of different models and rules in SAS Content Categorization Studio

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Text Analytics and Sentiment Mining Using SAS

COURSE AGENDA