Introduction for testing AI based systems

在构建、部署或测试基于人工智能的高质量系统时需要考虑什么

您将学到什么
了解 AI 的当前状态和预期趋势 为
基于 AI 的系统设计并执行测试计划和测试用例 为基于 AI 的系统
的测试策略做出贡献
了解与测试基于 AI 的系统相关的挑战，例如作为他们的自学能力、偏见、道德、复杂性、透明度
认识到测试人员在哪些方面可以最好地影响基于人工智能的系统的质量。

要求
建议具备软件测试和人工智能系统的基本知识，但本课程并非绝对必要

描述
测试基于 AI 的系统的非技术课程。对于任何正在考虑使用、构建或集成基于 AI 的系统的人来说都很有趣。

本课程将教您在构建、开发、部署、测试或仅使用基于人工智能的高质量系统时需要考虑的“什么”。我们要看看

– 什么是人工智能，什么是机器学习

– AI的现状

– 基于人工智能的系统的质量特征是什么

– 与基于人工智能的系统相关的挑战，例如自学系统

– 您可以采取哪些对策来影响质量

– 机器学习工作流程

– 您可以使用哪些方法和技术来测试基于 AI 的系统

– 为什么测试自动化可能不是您在 AI 测试中的首选。

完成整个课程后，您将能够为基于 AI 的系统创建测试计划、测试脚本和场景。您还可以确定哪些风险可能适用于您的特定 AI 项目，您可以监控机器学习工作流程并衡量项目或组织中使用的数据质量。此外，您将能够使用课程中讨论的测试方法和测试技术来实际执行基于 AI 的系统的测试。

本课程面向
对测试基于 AI 的系统感兴趣的软件测试人员
对质量感兴趣的机器学习工程师对质量 经理、产品所有者、产品经理
感兴趣的软件开发人员

What you need to take into consideration when building, deploying or testing high quality AI based system

Published 05/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 33 lectures (2h 16m) | Size: 601.6 MB

What you’ll learn
Understand the current state and expected trends of AI
Design and execute test plans and test cases for AI-based systems
Contribute to the test strategy for an AI-Based system
Understand the challenges associated with testing AI-Based systems, such as their self-learning capabilities, bias, ethics, complexity, transparency
Recognize where testers can best influence quality for AI based systems.

Requirements
Basic knowledge about software testing and AI systems is recommended, but not strictly necessary for this course

Description
A non-technical course on testing AI based systems. Interesting for anyone who is considering using, building, or integrating AI based systems.

This course will teach you the “what’s” you need to take into consideration when building, developing, deploying, testing or just using quality AI based systems. We are going to look at

– What is AI and what is ML

– The current state of AI

– What the quality characteristics for AI based systems are

– Challenges related to AI based systems, such as self-learning systems

– Which counter measures you can take to influence the quality

– The machine learning workflow

– Which methods and techniques you can use for testing AI based systems

– Why test automation might not be your first go-to in AI testing.

After you have completed the entire course, you will be able to create test plans, test scripts and scenarios for AI based systems. You can also identify which risks might be applicable for your particular AI project, you can monitor the Machine learning workflow process and measure the quality of data used within your project or organization. Furthermore you will be able to use the test methods and test techniques discussed in the course to actually execute tests for an AI based system.

Who this course is for
Software testers with an interest in testing AI based systems
ML engineers with an interest in quality
Software developers with an interest in quality
Managers, Product owners, Product managers