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Coursera

GenAI for Business Analysts: Faster Insights

Coursera Instructor Network via Coursera

Overview

This course is designed to introduce business analysts to the transformative capabilities of Generative Artificial Intelligence (GenAI). Learners will explore practical strategies to leverage GenAI in various business analysis tasks, enhancing efficiency and productivity. Through a combination of discussions, demonstrations, and hands-on activities, participants will gain a deep understanding of how GenAI can be integrated into business processes and decision-making. This course is tailored for business analysis managers, team leads, and business analysts who are keen to identify GenAI opportunities and guide their teams toward more efficient, innovative practices. Aspiring business analysts looking to future-proof their skills and gain a competitive edge by mastering the integration of GenAI in business analytics will also find this course valuable. Participants should be familiar with fundamental business analysis concepts and workflows, including business process modeling and requirements gathering, data handling with SQL, and analytics development with tools such as Tableau. An open mindset towards new technologies and a willingness to experiment and learn how GenAI can enhance business analytics workflows is essential. Whether you're an experienced business analyst looking to stay ahead of the curve or an aspiring professional seeking to future-proof your skillset, this course provides a foundation that will empower you to unlock new levels of efficiency, productivity, and creativity in your work.

Syllabus

  • GenAI for Business Analysts: Faster Insights
    • This course introduces business analysts to the transformative capabilities of Generative AI (GenAI), offering practical strategies to enhance efficiency and productivity in various tasks. Through discussions, demonstrations, and hands-on activities, participants will learn how to integrate GenAI into business processes and decision-making.

Taught by

Christopher Klaus

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