The Potentials and Pitfalls of AI and Machine Learning

Overview

Syllabus

• Introduction to AI and Machine Learning
Definitions and key concepts
Historical context and evolution
• Current State of AI in Various Industries
Healthcare
Finance
Manufacturing
Transportation
Retail
• Opportunities Presented by AI and Machine Learning
Enhancing productivity and efficiency
Enabling personalized services
Innovating new products and services
• Challenges of AI and Machine Learning
Technological limitations
Data privacy and security
Bias and fairness issues
• Ethical Considerations
Responsible AI use
Ensuring transparency and accountability
Addressing labor displacement concerns
• Practical Applications
Case studies and real-world examples
Tools and frameworks
• Future Trends in AI and Machine Learning
Emerging technologies
Potential societal impacts
Regulatory landscapes
• Concluding Panel Discussion
Recap of key insights
Open Q&A session
Future outlook and further reading
• Capstone Project
Development of an AI strategy for a selected industry
Presentation and peer feedback

---

Subjects

Conference Talks