Headlines

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  Course Orientation

  Understand CT-GenAI structure, how scenario questions work, and how to study using rationales.

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    Exam Expectations
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  1. Introduction to Generative AI for Software Testing

  Understand what GenAI is, what it can do for testers, and why it introduces new test risks and verification duties.

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    What CT-GenAI Expects from You as a Tester
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  2. Prompt Engineering for Effective Software Testing

  Write prompts that produce useful, verifiable test artifacts. Control output structure. Reduce ambiguity. Improve repeatability.

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    Verifying and Refining Prompts
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  3. Risks and Challenges of Using GenAI in Software Testing

  Manage reasoning errors, security and privacy risks, environmental impact, and regulatory obligations.

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    Energy Consumption and Environmental Impact
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    Regulations, Standards, and Best Practice Frameworks
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  4. LLM-Powered Test Infrastructure for Software Testing

  Understand the architecture and operating model for GenAI in testing: RAG, agents, fine-tuning, and LLMOps.

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    4.1 Retrieval-Augmented Generation (RAG) for Test Tasks
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    4.2 LLM-Powered Agents for Test Process Automation
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    4.3 Fine-Tuning and 4.4 LLMOps
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  5. Deploying and Integrating GenAI in Test Organizations

  Build a roadmap, prevent shadow AI, select LLMs/SLMs, estimate recurring costs, and manage change in roles and responsibilities.

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    5.1 Roadmap for Adoption
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    5.2 Manage Change