Automating Decision Workflows with AI

This course unlocks the next frontier of Decision Intelligence where AI meets automation to drive real-time, autonomous, and responsible decision-making at scale. You’ll learn to orchestrate multi-step processes, stream real-time insights, and build automated systems that boost accuracy, speed, and business impact. You’ll dive into Generative and Agentic AI to create autonomous, insight-driven decisions supported by strong ethical frameworks that keep every outcome transparent, fair, and accountable. Finally, you’ll master deploying and scaling these systems through MLOps, cloud APIs, and low-code platforms, making enterprise-ready automation efficient, scalable, and easy to adopt. By the end of this course, you will be able to: - Identify the key functions of intelligent automation pipelines for AI-driven decision-making. - Analyze Generative and Agentic AI models to design adaptive and autonomous decision workflows. - Evaluate responsible AI frameworks to ensure ethical and accountable automation practices. - Develop deployment strategies using MLOps and cloud technologies for continuous performance. - Design low-code and no-code solutions to expand and democratize Decision Intelligence adoption. This course is ideal for AI engineers, data scientists, automation architects, and business technology leaders who want to bridge AI innovation with scalable automation. A foundation in Decision Intelligence or machine learning will enhance your learning experience. Join this course to master the integration of AI, automation, and responsibility and learn to build decision systems that think, act, and evolve with intelligence

• Identify automation and orchestration principles in AI-powered decision systems
• Analyze generative and agentic AI techniques for autonomous decision-making
• Evaluate responsible AI frameworks for fairness and transparency
• Develop scalable low-code deployment strategies with MLOps and cloud APIs

• Basic familiarity with relevant terminology and concepts
• Readiness for practical application exercises