Training Areas
A Few of the Key Areas Covered in the A-Z Training Cohorts..
AI Product Implementation
Gen AI and Agentic AI Overview
Get an overview of what’s entailed in these main areas to make Informed Product Implementation Path decisions
Crafting an AI Business Value Case
A gap in knowledge and expertise of the value AI technologies deliver is leading to implementations that aren't realizing business returns. Don’t just ‘Do AI’, create business value with AI.
Assessing Technical AI Implementation Complexity
The technology stack and science techniques for implementing Accurate and Reliable AI Products is complex. Before embarking on implementation, it is critical to understand this complexity and choose the right path for your business model goals.
Validating Target Market and End User AI Product Adoption
Just building an AI product, does not automatically guarantee that customers with use it and love the experience. Mitigate the chances that your AI implementation does not resonate with your target audience.
AI Product Risk, Governance and Regulation
Depending on the Industry you're in, getting an AI product to market entails much more than plugging in an AI model and declaring the product ready for customers. There are real Governance items that, if not done properly, introduce risk to your customers, costing your business financially and reputationally.
The AI Product Implementation Roadmap
AI Product Development is unlike Traditional Software Development. Train your teams on AI product development and successful A-Z implementation Roadmaps.
AI Data Readiness for High-Quality Model Output Performance
A not-so-secret on what makes highly reliable and accurate AI product experiences for end users: Your AI product is only as good as the curation quality of the data. No matter how powerful the model you buy or build is. Garbage in, garbage out.
