Rajiv Shah helps AI teams build the right thing

Helped me step back from the lets go build it to lets think of why we need to do it. As Simon Sinek mentioned in his book "Why", every initiative should start with the Why. Rajiv has translated his multi decade experience to frameworks likes GOATS loop that help you define the why and also anticipate the challenges and prevent common pitfalls during the development of AI agents.

Exceptional content that I've never seen elsewhere. Content is really insightful.

A very insightful course with practical takeaways. I'm looking forward to applying what I learned to help drive our AI strategy

This is a timely and valuable course worthy or your time and expense. The Domain Specific Checklists alone justify it because you can use them immediately in your work. I especially appreciated Lessons 3 & 4, which lie at the heart of the course. While the course covers the landscape of AI problem types, learners with some pre-existing familiarity with applied AI will benefit the most. You don't need to be a practitioner, but you don't want this to be your first exposure to the material. We are all becoming AI managers, which means our decision-making skills are our most valuable (and marketable) skills. This course hones those within the context of applied AI, which makes it particularly relevant for AI practitioners and decision-makers.

My attitude to AI projects has completely transformed as a result of this training. It stresses defining the proper problem rather than concentrating on models first, which is, as I now understand, where most AI initiatives fall short. Particularly useful is the "Loop" architecture, which offers an organized and transparent method for defining issues, weighing trade-offs, and agreeing on success measures prior to doing anything. The teachings are further made applicable and practical by the real-world case studies. All things considered, this course is perfect for anyone who wish to approach AI more strategically rather than only creating models.