The Science Behind AI for Customer Experience | Free Course

Take this course

• CX and Insights teams who want to understand how AI analyzes feedback and turns it into actionable insights
• Product teams looking to make sense of the AI landscape and how it applies to feedback analysis
• Data Science and Research teams who want a deeper understanding of the technical approaches in AI for CX

AI for Feedback Analysis

Discover how AI has evolved and what's driving today's breakthroughs.

Rule-Based Lexicons

Learn how lexicon-based systems work, their advantages, and their limitations.

Thematic Analysis

See how neural networks cluster feedback into themes and where this approach falls short.

Large Language Models

Understand the strengths and limitations of large language models for feedback analysis.

Chattermill's Lyra AI

Explore what makes Chattermill's approach to feedback analysis unique and the key technologies behind it.

The Future & AI Agents

Find out what AI agents are, how they've evolved, and what they mean for the future of CX.

1. Introduction

   1. The Science Behind AI for CX

2. Overview of AI for CX

   1. Overview of AI
   2. Recent Advances in AI
   3. Rule-Based Lexicon
   4. Thematic Analysis & Neural Embeddings
   5. Large Language Models (LLMs)

3. Chattermill's Approach to Customer Feedback Analysis

   1. The Use of LLMs & Gen AI in Chattermill
   2. Introducing Lyra AI

4. The Future of AI for CX

   1. AI Agents
   2. Overview & History of Agentic Systems

5. Summary

   1. Summary

6. Assessment

   1. Take the assessment

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About this course

• Free
• 12 lessons
• 0.5 hours of video content

Aji Ghose serves as Chief Scientist at Chattermill, overseeing Data Science, MLOps, and MLEng, focused on unearthing actionable insights from customer feedback. Aji earned his PhD in Computational Cognitive Science, specialising in multimodal deep learning, from Birkbeck, University of London. He holds an MSc in Computer Science with Artificial Intelligence from the University of York. Aji also serves as a chair and lecturer for Data Science, Statistics, and AI courses at the Market Research Society.

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