Project Cycle Glossary

Project Cycle
Problem Scoping
Data Acquisition
Data Exploration
Project Manager
Project Stakeholder
Agile Management
Project Budget
Project Life Cycle
Gantt Chart
Change Management
Project Timeline
Resource Allocation
Risk Management

What is Project Cycle ?

Project Cycle is an appropriate framework which can lead us towards developing an AI Project.

If you are developing or creating a project you need to go through some steps which are required to complete the project.
For example: You want to make tea.

Making Tea

  1. Boil Water .
  2. Put Tea Powder
  3. Put Milk
This was a simple one which was only consisting exploring the items and modelling it into tea. Lets see one more example:

Creating a birthday card.

  1. Checking the factors like budget,etc Which will help us decide the next steps and understanding the Project.
  2. Acquiring data from different sources like onlin, with friends etc for Designs and ideas.
  3. Making a list of the gathered data.
  4. Creating or Modelling a card on the basis of the data collected.
  5. Showing it to Parents or cousins to Let them check it or evaluate it.

Components of Project Cycle

Components of the AI Project Cycle are:

  1. Problem Scoping
  2. Data Acquisition
  3. Data Exploration
  4. Modelling
  5. Evaluation

Problem Scoping

Problem Scoping refers to understanding a probkem finding out various factors which affect the problem, define the goal or aim of the project.

4Ws Of Problem Scoping

The 4W's of Problem Scoping are Who, What, Where and Why. These Ws helps in identifying and understanding the probem in a better and efficient manner.

1. Who - "Who" part helps us in comprehenting and categorizing who all are affected directly and indirectly with the problem and who are called the Stake Holders

2. What - "What" part helps us in understanding and indentifying the nature of the problem and under this block, you also gather evidence to prove that the problem you have selected actually exists.

3. Where - "Where" does the problem arises, situation and the location.

4. Why - "Why" is the given problem worth solving.

Data Acquisition

Data Acquisition is he process of collecting accurate and riliable data to work with. Data Can be in the format of text, video, images, audio and so on and it can be collected from carious sourcs like the interest, journals, newspapers and so on.

Data Exploration

Data Exploration is the process of arranging the gathered data uniformaly for a better understanding. Data can be arranged in the form of a table, plotting a chart or making database.

Modelling the Project

Modelling is the process in which different models based on the previous components can be created and even checked for the advantages and disadvantages of the model.


Evaluation is the method of understanding the reliability of an API Evaluation and is based on the outputs which is received by the feeding the data into the model and comparing the output with the actual answers.

API Stands for Application Programming Interface