CBSE Class 10th AI (Artificial Intelleigence) | 3. Introduction to AI Project Cycle by Abraham | Learn Smarter
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3. Introduction to AI Project Cycle

The AI Project Cycle is a systematic method for developing AI solutions, encompassing stages from problem identification to evaluation. It emphasizes the importance of ethical practices and enables students to build practical AI applications. The iterative nature of the cycle allows for continuous improvement and adaption based on insights gained.

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Sections

  • 3

    Introduction To Ai Project Cycle

    The AI Project Cycle is a systematic methodology for addressing real-world problems using AI techniques, encompassing five critical phases.

    Learning Practice

  • 3.1

    What Is The Ai Project Cycle?

    The AI Project Cycle is a systematic approach to developing AI solutions, ensuring effective problem-solving through structured phases.

    Learning Practice

  • 3.2

    Phases Of The Ai Project Cycle

    The AI Project Cycle consists of five major phases that guide the development of AI solutions from problem identification to evaluation.

    Learning Practice

  • 3.2.1

    Problem Scoping

    Problem scoping is the first step in the AI Project Cycle that involves identifying and understanding the problem to be solved.

    Learning Practice

  • 3.2.2

    Data Acquisition

    Data acquisition is the process of gathering relevant data after defining a problem in the AI project cycle.

    Learning Practice

  • 3.2.3

    Data Exploration

    Data Exploration involves understanding and preparing data before modeling in AI projects.

    Learning Practice

  • 3.2.4

    Modelling

    The Modelling phase of the AI Project Cycle involves selecting and training AI models to make predictions based on data.

    Learning Practice

  • 3.2.5

    Evaluation

    Evaluation is a critical phase in the AI Project Cycle that involves assessing the performance of the AI model using various metrics.

    Learning Practice

  • 3.3

    Importance Of Iteration In The Ai Project Cycle

    Iteration is crucial in the AI project cycle, allowing teams to refine their approach based on insights gained at each step.

    Learning Practice

  • 3.4

    Ethical Considerations In The Ai Project Cycle

    This section emphasizes the importance of ethical practices in every stage of the AI Project Cycle.

    Learning Practice

References

Chapter_3_Introd.pdf

Class Notes

Memorization

What we have learnt

  • The AI Project Cycle consis...
  • Effective AI solutions must...
  • The iterative process is ke...

Final Test

Revision Tests