Building Bespoke AI Solutions
This course supports organizations in designing, testing, and deploying bespoke AI models. It covers key stages of AI solution development, including scoping, data preparation, model development, and implementation. The focus remains on business outcomes, enabling leaders and teams to engage confidently with data science and technology partners.
Learning Objectives
By the end of this course, participants will be able to:
- Differentiate between off-the-shelf AI tools and bespoke models.
- Understand the stages of AI solution development from design to deployment.
- Identify data requirements and challenges for building effective models.
- Recognize the importance of clean, structured, and representative datasets.
- Explore model training, testing, and validation in accessible business terms.
- Understand how APIs and integrations allow AI models to fit into workflows.
- Learn best practices for working with vendors and in-house data science teams.
- Explore case studies of successful bespoke AI implementations in finance.
- Identify potential risks of overfitting, bias, or poor adoption.
- Develop a business case for building bespoke AI solutions that align with strategic goals.
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