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Data Science & Machine Learning:5 Day POC Workshop

cloudThing

5-day Data Science and Machine Learning Discovery envisioning POC To understand the potential of AI in Azure or focus on a specific project with your key stakeholders

AI projects carry an element of risk, given the uncertain ROI and the emerging technologies involved. A structured approach to enable a business to understand AI potential within their organisation is required, identifying specific project opportunities with quantifiable benefits. To discover the optimal approach for a pilot implementation, CT recommends a first principles discovery process and envisioning to scope potential projects in Azure. Prior to the workshop we will have an initial discovery call between senior stakeholders & CT Predictive Science representatives. We will acquire an understanding of current business priorities and desired future states. The outcome of this call is a list of areas to focus on in the workshop.

Days 1 & 2 - Envisioning Session This will include discussions about organisational requirements and capabilities, and availability and quality of relevant data. For each potential project area identified, we will help frame the business problem as a quantifiable proposal refined on to our predictive science canvas. The outcome will be a shortlist of project ideas, with an order of magnitude estimate of implementation effort and potential business impact.

Days 3 & 4 - Feasibility Study
Based on the project shortlist, one AI project idea will be selected to be turned into a concrete proposal for a pilot. To develop this, CT will undertake a feasibility study consisting of a short cycle of analysis and exploration of provided sample data.

Day 5 - Proposal Handover
Having built a comprehensive shared understanding of the power and the limitations of AI, we will deliver a proposal for a pilot project and deliver as a Show & Tell format. The pilot is a secure, production-ready and Azure based supported solution that proves the project idea and solidifies the business case for further collaboration and investment.

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