GenAI Life Cycle for Business Professionals

Overview

Generative AI for Business Leaders:

The Complete Implementation Guide

Syllabus

• Introduction to Generative AI
Overview of AI and its impact on business
Understanding Generative AI: Capabilities and Limitations
Key differentiators between traditional AI and Generative AI
• Identifying Business Opportunities for Generative AI
Assessing business needs and opportunities
Real-world examples of Generative AI applications
Ethical considerations and risk management
• The Generative AI Development Lifecycle
Defining project goals and success metrics
Data collection and preprocessing
Model selection and training
• Implementing Generative AI Solutions
Integrating AI into existing business processes
Collaborating with technical teams and AI specialists
Monitoring performance and iterating on solutions
• Post-Implementation Strategies
Evaluating and measuring business impact
Continuous AI model improvement and updating
Managing change and driving adoption
• Best Practices and Case Studies
Lessons learned from successful AI implementations
Avoiding common pitfalls in AI projects
Case studies and industry insights
• Future Trends in Generative AI
Emerging technologies and innovations
Preparing for the future of AI in business
Building a strategic roadmap for AI evolution
• Conclusion and Next Steps
Recap of key concepts
Resources for further learning
Actionable steps to begin AI implementation in your organization

Taught by

Yash Thakker

Subjects

Computer Science