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- AI
Generative AI Project Pitfalls & Solutions
1 Course
0.5 Hours
Skill IQ
Generative AI projects often fail due to unclear goals, unreliable outputs, and overlooked risks around data, evaluation, and workflow design. Understanding these pitfalls is critical to successfully using generative AI in real-world scenarios.
This path covers everything from identifying common generative AI project failures to applying practical solutions for improving reliability, governance, and outcomes. You’ll learn best practices for planning, evaluating, and scaling generative AI projects using modern AI tools and platforms.
Content in this path
Generative AI Project Pitfalls & Solutions
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What You'll Learn
- How to align stakeholders around generative AI goals and expectations
- How to identify and mitigate hallucinations and improve retrieval reliability in generative AI systems
- How to establish data quality standards and ground truth for generative AI
- How to apply responsible generative AI practices for safety, ethics, and compliance
- How to optimize generative AI systems for speed, stability, and performance
- How to design and evaluate reliable AI agent workflows
Prerequisites
- There are no prerequisites for this path.
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