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Starts 6 July 2025 03:09

Ends 6 July 2025

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The Reality of Testing an Artificial World

Join us for an insightful exploration into the realities of testing in artificial intelligence. This session uncovers the unique challenges and essential strategies for effectively evaluating AI-driven applications. As AI continues to revolutionize software development, gaining expertise in rigorous testing methodologies becomes crucial. Ou.
WeAreDevelopers via YouTube

WeAreDevelopers

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Overview

Join us for an insightful exploration into the realities of testing in artificial intelligence. This session uncovers the unique challenges and essential strategies for effectively evaluating AI-driven applications.

As AI continues to revolutionize software development, gaining expertise in rigorous testing methodologies becomes crucial.

Our discussion will equip you with the knowledge to navigate this evolving landscape with confidence.

Hosted by the University, this presentation is an invaluable opportunity for professionals looking to enhance their skills in artificial intelligence testing. Access the talk on YouTube, as part of a series of Artificial Intelligence Courses and Conference Talks.

Syllabus

  • Introduction to AI Testing
  • Overview of AI-driven applications
    Importance of testing in AI systems
    Differences between AI and traditional software testing
  • Challenges in Testing AI Applications
  • Unpredictability of AI behavior
    Handling large datasets and complex models
    Bias and fairness considerations in AI systems
    Continuous learning and adapting models
  • Testing Strategies for AI Systems
  • Developing test cases for AI applications
    Verification and validation of AI models
    Testing AI algorithms against ethical guidelines
    Handling model drift and updating test scenarios
  • Tools and Techniques for AI Testing
  • Exploring testing frameworks and tools for AI
    Automated testing for AI models and systems
    Performance testing for scalability and reliability
    Utilizing simulation environments for AI testing
  • Case Studies and Best Practices
  • Reviewing real-world examples of AI testing
    Lessons learned from industry practices
    Effective documentation for AI testing processes
  • Preparing for a Career in AI Testing
  • Skills and knowledge required for AI testing roles
    Future trends and the evolving landscape of AI testing
    Building expertise through continuous learning and practice
  • Conclusion and Next Steps
  • Recap of key concepts in AI testing
    Exploring additional resources and advanced topics
    Engaging in community and professional networks related to AI testing

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