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Engineering Data Systems for Modern Analytics

Data systems now operate at unprecedented scale and speed, while facing new expectations around efficiency, sustainability, and governance. Organizations need professionals who can design cloud-native pipelines that support analytics and AI without sacrificing reliability, transparency, or resource responsibility. This certificate will prepare learners to architect and manage production data systems that enable forecasting, visualization, and evidence-based decision-making in modern cloud environments.

The curriculum integrates data engineering, forecasting, and analytics visualization within modern cloud platforms. In the Data Engineering and Cloud Analytics certificate, students gain hands-on experience designing cloud-native pipelines, developing predictive and operational models, and translating complex data into clear, actionable insights. Emphasis is placed on reproducibility, ethical practice, and energy-efficient computing, ensuring graduates can support scalable analytics while managing cost, performance, and environmental impact. Graduates are prepared for roles across data engineering, analytics engineering, business intelligence, and data systems architecture in a wide range of industries.

The Master's Certificate in Data Engineering and Cloud Analytics will allow you to:

• Engineer Reproducible Systems: Design and automate ML workflows with CI/CD and monitoring frameworks.
• Implement Responsible AI: Integrate ethical, privacy, and environmental governance into ML systems. 
• Leverage Generative AI: Apply and evaluate LLMs responsibly within analytics and decision workflows.
• Deploy Scalable Infrastructure: Architect cloud pipelines optimized for performance, cost, and sustainability.

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