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SDLC has the following stages:
Requirement
Analysis
System Design
Implementation
Testing
Deployment
Maintenance
As you can see in the above diagram, the first stage is Requirement Analysis. It is the stage where we have to
analyse the required data and information. The next stage is System Design in which we design data flow diagrams
like flowcharts from the analysed data to demonstrate the flow of data in the software to be developed. The next
stage is Implementation in which the real programs are written. After developing the programs, we need to test
the written programs to solve the problem for which the programs are written. If the program is tested successfully
then the software is deployed in the client location.
Similar to SDLC, the AI project cycle is the process of converting the real-life problem into an AI-based model. The
project cycle framework is designed to help project managers guide their projects successfully from start to end.
The purpose of the project life cycle is to create an easy-to-follow framework to guide projects. The AI project cycle
provides us with an appropriate framework which can lead us towards our goal.
Stages in an AI Project Cycle
The AI project cycle involves several key stages, each building upon the previous one to develop, deploy, and
maintain an AI system effectively. These stages are as follows:
Problem
Scoping
Data
Deployment
Acquisition
Data
Evaluation
Exploration
Modelling
188 Touchpad Artificial Intelligence (Ver. 3.0)-IX

