- This course focuses on interaction AI, which enhances the ability of businesses to engage with customers and improve internal communication through intelligent conversational agents, chatbots, and virtual assistants. Students will learn how to integrate AI into customer service, marketing, and operations to create innovative business solutions.
- Level: Intermediate
- Prerequisites: Basic understanding of AI, no coding required.
- Assessments: Weekly Micro Assessments, Final Project-based Assessment.
- Job Roles Applicability: Business Innovation Specialist, Customer Experience Manager, AI Strategist, Product Manager.
Week 1 - Introduction to Interaction AI in Business
Learning OutcomeUnderstand the basics of interaction AI and its applications in business innovation.
1.1 What is interaction AI and its relevance to business?1.2 Key AI-driven interaction technologies (chatbots, virtual assistants, conversational AI).
1.3 Examples of interaction AI in various industries (e.g., customer service, e-commerce).
Practical Component
Demonstrate an AI-powered chatbot interacting with a customer query in a simulated business setting.
Week 2 - Designing AI-Powered Conversational Interfaces For HR and Finance
Learning OutcomeLearn how to design user-friendly and effective conversational interfaces for businesses.
2.1 Principles of conversational design with LLMs and beyond through interactive principles2.2 Understanding intent, entity recognition, and dialogue management. .
2.3 Designing voice and text-based interactions for business needs with customisation of LLMs
Practical Component
Use Cases for Human Resources, and Interaction roles for various areas of Business.
Week 3 - Integrating AI into Customer Service and Support
Learning OutcomeExplore how AI can transform customer service operations and improve customer satisfaction.
3.1 AI-powered customer support systems (chatbots, automated service agents).3.2 Enhancing customer experience with AI (personalization, problem resolution, visualisation with Deep fakes).
3.3 Best practices for AI-driven customer service integration.
Practical Componenet
Implement a customer service bot that can handle common queries and provide basic troubleshooting.
Week 4 - AI for Sales and Marketing Interactions
Learning OutcomeUnderstand how interaction AI can be used to drive sales, marketing, and customer engagement.
4.1 AI-driven sales assistants and lead generation tools.4.2 Personalized marketing strategies using interaction AI.
4.3 Using AI to understand customer preferences and behavior for better targeting.
Practical Componenet
Create an AI-based sales assistant for personalized product recommendations.
Week 5 - Advanced Interaction AI Techniques for Business Innovation
Learning OutcomeLearn about advanced techniques in AI interactions, including natural language processing and voice assistants.
5.1 Voice-based AI and its business applications.5.2 Understanding sentiment analysis for improving customer interactions.
5.3 Incorporating machine learning to enhance AI-driven interactions over time.
Practical Component
Implement sentiment analysis in a chatbot to understand customer emotions during interactions.
Week 6 - Final Project and Assessment
Learning OutcomeApply interaction AI techniques to a business scenario, demonstrating how AI can be used to improve customer engagement and operational efficiency.
6.1 Final project: Build a complete AI interaction system for a business (e.g., a virtual assistant for e-commerce or customer support).6.2 Peer reviews and feedback on projects.
6.3 Final assessment of the project based on design, functionality, and business impact.
Practical Component
Present the AI interaction system and demonstrate its effectiveness in improving business operations.