Generative AI in NLP

Description:

This interactive workshop delves into the fascinating realm of sentiment analysis using artificial intelligence, providing participants with the essential knowledge to understand and apply AI techniques for interpreting emotions in text data. Whether you have prior coding experience or not, this workshop will guide you through the core concepts and practical applications of sentiment analysis. You'll learn how AI algorithms analyze textual content to determine sentiments, enabling you to harness these insights for various purposes such as customer feedback analysis, social media monitoring, and market research. Through hands-on exercises and real-world examples, you'll gain the skills needed to leverage AI for extracting valuable emotional insights from text data.

Course Code: BDT360

Duration : 2 Days

Learning Objectives

• Gain a foundational understanding of sentiment analysis using AI
• Identify real-world applications of sentiment analysis
• Explore user-friendly AI tools for text analysis
• Develop your problem-solving skills through collaborative projects

• Basic Computer Literacy
• Interest in AI and Text Analysis
• Understanding of Basic Data Concepts

• Marketing professionals
• Customer service representatives
• Business analysts
• Anyone curious about the power of AI in understanding human emotions through text

• Marketing professionals
• Customer service representatives
• Business analysts
• Anyone curious about the power of AI in understanding human emotions through text

Course Outline:

Module 1: Introduction to Sentiment Analysis

• Overview of Sentiment Analysis
• Definition and Importance
• Applications in Various Industries

Module 2: Basics of AI in Text Analysis

• Foundational Concepts of AI
• Understanding Machine Learning and NLP
• Role of AI in Analyzing Text Data

Module 3: Sentiment Analysis Techniques

• Text Preprocessing
• Tokenization, Lemmatization, and Stop Words
• Sentiment Classification
• Rule-Based Methods
• Machine Learning Approaches

Module 4: Practical Applications

• Customer Feedback Analysis
• Case Studies and Examples
• Social Media Monitoring
• Techniques and Tools
• Market Research
• Extracting Insights from Text Data

Module 5: Hands-On Exercises

• Implementing Sentiment Analysis
• Using AI Tools for Sentiment Analysis
• Analyzing Sample Text Data
• Interpreting Results and Drawing Conclusions

Module 6: Ethics and Challenges in Sentiment Analysis

• Bias in Data and Algorithms
• Ensuring Ethical Use of AI