Machine Learning & AI: 4-Hour Workshops

SFL Scientific

Accelerate AI adoption and uncover key opportunities, strategic decisions, and technical feasibility.

Connecting AI technology to Business Value: SFL Scientific provides AI & ML custom workshops and use case labs to accelerate AI adoption and improve performance. Through this accelerated adoption we aim to help clients understand the capabilities of the AzureML suite and how it can be leveraged to achieve their organizational goals. Specific toolsets within ML Studio we cover are SDK for Python, CLI, Ray RLlib, and Many Model Solutions Accelerator.

These sessions are tailored to address business challenges and are often the first step in developing a comprehensive data strategy and AI roadmap. The goal is to jump-start and deep-dive into use cases—short and long-term business objectives—with the intent to uncover data assets, define metrics, people, execution environments, delivery methods, and engage leaders in the organization to begin to map available or custom AI solutions to deliver increased value to the organization.

Typical Organizational goals for AI may include:
 
 - Creating new business models, products, and services that use data to predict, measure, and verify specific outcomes or decisions.
 - Use predictive monitoring of key processes, assets, or expenditures across business lines (production, supply, R&D, etc.) to optimize investments and capital allocation.
 
 - Create tools to enable workforce efficiency and reduce operating costs.

Target Audience: To accelerate AI adoption, organizations will need access to the right data sets, the ability to train algorithms on that data, and as critically, professionals who can execute. Putting in place machine learning models, dynamic data pipelines, developing the workflows, governance, storage, and architecture necessary will require a dedicated team and partners. Sessions are appropriate for executives, innovation and product managers, IT professionals, data scientists, and engineers who are looking to apply or expand AI within their organization.

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