R Language
Principles of Effective Data Storytelling
Data Analysis for Predictive Modeling
Data Visualization Basics
Data Visualization Tools for Analysts
Extraction
Understanding Customer Needs
Advanced Visualization Techniques in Data Analysis
Customer Feedback 
Sentiment Analysis: Uses natural
language processing to gauge customer emotions from textual feedback
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Principles of Effective Data Storytelling 
Avoid Jargon: Use plain
language that everyone can understand
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Data Analysis for Predictive Modeling 
Neural Networks Model inspired by the human brain Image recognition, natural
language processing Model Training and Testing After selecting a model, it is trained using a training dataset
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Data Visualization Basics 
Python - Programming
language with libraries like Matplotlib and Seaborn for data visualization
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Data Visualization Tools for Analysts 
Key Features: Data modeling capabilities Integration with Excel Natural
language queries Use Cases: Operational reporting Customer insights Performance metrics analysis 3
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Extraction 
AI and NLP: Leveraging artificial intelligence and natural
language processing to improve the extraction of unstructured data
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Understanding Customer Needs 
Sentiment Analysis Tools: Natural
language processing tools can analyze customer feedback for sentiment, helping to gauge overall satisfaction
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Advanced Visualization Techniques in Data Analysis 
R - A programming
language and free software environment for statistical computing and graphics
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Tools 
Academic research, data science projects Python Versatile programming
language, libraries like Pandas and NumPy Data analysis, machine learning Data Mining Tools Data mining tools are designed to discover patterns and relationships
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Maximizing Value through Data Analysis 
Python - A programming
language that offers extensive libraries for data analysis and machine learning
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