LLMs for Sentiment Analysis Training Course
Large Language Models (LLMs) are deep neural network architectures capable of generating natural language texts in response to specific inputs or contexts.
This instructor-led, live training (available online or onsite) is designed for intermediate-level data and marketing professionals aiming to leverage LLMs to analyze and interpret public sentiment across diverse text sources, including social media posts, product reviews, and customer feedback.
Upon completion of this training, participants will be able to:
- Grasp the core principles of sentiment analysis and its application via LLMs.
- Preprocess and prepare datasets tailored for sentiment analysis.
- Train and fine-tune LLMs to accurately capture sentiment within text.
- Analyze sentiment in real-time from social media and other textual sources.
- Integrate insights from sentiment analysis into business strategies and decision-making frameworks.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
Course Outline
Introduction to Sentiment Analysis
- Fundamentals of sentiment analysis
- Challenges and opportunities in sentiment analysis
- Overview of LLMs and their capabilities
LLMs and Natural Language Understanding
- Deep dive into LLMs architecture
- Understanding context and sentiment with LLMs
- Preprocessing data for sentiment analysis
Building Sentiment Analysis Models with LLMs
- Training LLMs for sentiment analysis
- Fine-tuning models for specific domains
- Practical exercises on model training
Analyzing Social Media with LLMs
- Collecting social media data for analysis
- Real-time sentiment tracking on social platforms
- Case studies of social sentiment analysis
Sentiment Analysis in Customer Feedback
- Extracting insights from customer reviews and surveys
- Enhancing customer service with sentiment analysis
- Workshop on feedback analysis
Advanced Topics in Sentiment Analysis
- Addressing sarcasm, irony, and complex emotions
- Cross-language sentiment analysis
- Future trends in sentiment analysis with LLMs
Ethical Considerations and Bias Mitigation
- Ethical implications of sentiment analysis
- Identifying and mitigating bias in models
- Responsible use of sentiment analysis
Project and Assessment
- Analyzing sentiment from a chosen dataset
- Peer reviews and group discussions
- Final assessment and feedback
Summary and Next Steps
Requirements
- Understanding of basic machine learning concepts
- Experience with text data preprocessing and analysis
- Familiarity with Python programming
Audience
- Data scientists and analysts
- Marketing professionals
- Product managers
Open Training Courses require 5+ participants.
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