ChatGPT: Performance Monitoring and Optimization

Course Info

Date: Dec-09-2024

Length: 1 Week

City: Paris

Fees: 4,350

Type: In Classroom

Available Dates

  • Dec-09-2024

    Paris

  • Jan-13-2025

    Paris

  • Feb-10-2025

    Paris

  • Mar-10-2025

    Paris

  • Apr-14-2025

    Paris

  • May-12-2025

    Paris

  • June-09-2025

    Paris

  • July-14-2025

    Paris

  • Aug-11-2025

    Paris

  • Sep-08-2025

    Paris

  • Oct-13-2025

    Paris

  • Nov-10-2025

    Paris

  • Dec-08-2025

    Paris

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  • Nov-25-2024

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  • Nov-25-2024

    Dubai

  • Dec-02-2024

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  • Dec-02-2024

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  • Dec-09-2024

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  • Dec-16-2024

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  • Dec-30-2024

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  • Dec-30-2024

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  • Sep-29-2025

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  • Oct-06-2025

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  • Oct-13-2025

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  • Nov-24-2025

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  • Nov-24-2025

    Dubai

  • Dec-01-2025

    Istanbul

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    Kuala Lumpur

  • Dec-08-2025

    Singapore

  • Dec-15-2025

    Amsterdam

  • Dec-15-2025

    London

  • Dec-22-2025

    Barcelona

  • Dec-29-2025

    Kuala Lumpur

  • Dec-29-2025

    Dubai

  • Dec-29-2025

    Istanbul

Course Details

Course Outline

5 days course

Introduction to Performance Monitoring in AI Systems 


  • Understanding the importance of monitoring AI systems in real-time
  • Exploring key metrics for ChatGPT performance
  • Overview of tools for monitoring AI performance:


  1. OpenAI API dashboard
  2. Custom solutions


  • Analyzing real-world examples of AI performance monitoring
  • Steps of setting up basic monitoring for a ChatGPT deployment

Real-Time Performance Tracking and Analysis


  • Steps of implementing real-time performance tracking for ChatGPT
  • Techniques for analyze logs for insights into performance and user interactions
  • Process of creating custom dashboards for visualizing performance metrics
  • Techniques to build and configure a real-time monitoring dashboard
  • Discussing best practices for maintaining continuous monitoring

Troubleshooting and Error Handling

 

  • Identifying common performance issues in ChatGPT deployments
  • Strategies for error handling: Retries, fallbacks, and user notifications
  • Steps of conducting root cause analysis using logs and performance data
  • Simulating errors and practicing troubleshooting techniques
  • Reviewing case studies on resolving AI performance issues

Optimization Strategies for ChatGPT


  • Ways of optimizing prompt engineering to improve response quality
  • Exploring fine-tune models that enhance performance
  • Steps of scaling ChatGPT deployments to handle increased load
  • Best practices for Implementing optimization strategies in a live deployment
  • Discussing long-term strategies for maintaining AI performance

Continuous Monitoring and Improvement 


  • Identifying the importance of continuous monitoring and improvement
  • Methods for developing a framework for continuous performance monitoring
  • Ways of automating monitoring processes with tools and scripts
  • Reviewing case studies and industry best practices
  • Designing and deploying a comprehensive monitoring framework
  • Final presentation and feedback