Developing Generative Artificial Intelligence Solutions
In this course, you will explore the generative artificial intelligence (generative AI) application lifecycle, which includes defining a business use case, selecting a foundation model (FM), improving the performance of an FM, evaluating the performance of an FM, and deployment and its impact on business objectives. This course is a primer to generative AI courses, which dive deeper into concepts related to customizing an FM using prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning.
-
0 Lessons
-
Fundamental
-
50 minutes
- Category AI
In this course, you will explore the generative artificial intelligence (generative AI) application lifecycle, which includes defining a business use case, selecting a foundation model (FM), improving the performance of an FM, evaluating the performance of an FM, and deployment and its impact on business objectives. This course is a primer to generative AI courses, which dive deeper into concepts related to customizing an FM using prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning.
- Generative AI solution design and lifecycle mapping
- Foundation model selection and evaluation
- Model performance optimization techniques
- Business impact assessment of deployed AI systems
- Learn how to define AI business use cases and map them to foundation model capabilities
- Understand how to evaluate and improve the performance of generative AI models
- Gain clarity on deployment workflows and how generative AI impacts business goals
- Interactive learning elements including videos and visual examples
- Step-by-step walkthrough of a generative AI application lifecycle
- Primer on advanced concepts like prompt engineering, RAG, and fine-tuning
- Certificate of completion
