AI Python Zero-to-Hero: Build a Customer Feedback Analyzer
Key Takeaways:- Learn how to analyze customer feedback using sentiment analysis and AI text summarization.
- Discover how to turn data analysis results into actionable business intelligence.
- Explore how AI can assist in generating Python code to streamline analysis workflows.
Description
Understanding customer feedback is essential for making informed business decisions, but analyzing large volumes of text data can be a challenge. By combining data analysis, sentiment analysis, and AI-driven text summarization, you can quickly transform raw feedback into actionable insights. Learning how to integrate AI into your workflow can further streamline the process, saving time and improving accuracy.
In this third session , Francesca Donadoni, Curriculum Manager for Artificial Intelligence at DataCamp, will guide you through building your own customer feedback analyzer. You’ll learn how to use sentiment analysis and text summarization to extract insights from feedback, transform analysis results into actionable intelligence, and leverage AI to generate Python code for business intelligence tasks. This session is perfect for data and business analysts looking to enhance their ability to turn customer feedback into strategic decisions.
Presenter Bio
Francesca is an AI Curriculum Manager at DataCamp, where she works to create courses, content, and solutions for AI learning. She has a keen interest in inclusive and accessible AI-based technologies.
After graduating from Imperial College London in 2014, she earned a master's and PhD in Bioengineering at UCL. She spent two years at Northwell Health Labs in the US developing algorithms with clinical data, then returned to London to work as a Machine Learning and AI Engineer with startups before joining DataCamp.