Artificial Intelligence projects don’t just “happen.” They follow a structured path called the AI Project Cycle. This cycle provides a step-by-step approach to solving problems with AI, ensuring that the system is accurate, ethical, and useful. Understanding the AI Project Cycle is important because it helps learners, developers, and businesses build AI solutions in a systematic and responsible way.
1. The AI Project Life Cycle: How Ideas Become Intelligent Systems
- Why We Need an AI Project Life Cycle
- Importance OF AI Project Life Cycle
- Limitations of the AI Project Life Cycle
2. Stages of the AI Project Cycle
- Problem Scoping
- Data Acquisition
- Data Exploration
- Modelling
- Evaluation
- Deployment
- Human Feedback in Iteration