Harnessing Generative AI for Business Innovation
Generative AI & Applied Prompt Engineering

Harnessing Generative AI for Business Innovation

This level provides a practical guide to using generative AI for business automation, product design, and workflow enhancement. Learners will explore prompt design frameworks, evaluation metrics, and engage with case studies for hands-on experience.

5 hours and 20 minutesBusiness and TechnologyIntermediate80 topics1 enrolment

Learning Objectives

Equip learners with the skills to effectively apply generative AI in real-world business scenarios, enhancing automation, design, and workflows through proficient prompt engineering.

Chapters

Introduction to Generative AI in Business

Explore the role of generative AI in transforming business processes and innovation.

Goal:Understand the foundational concepts of generative AI and its application in business.

Learn the principles of crafting effective prompts for generative AI applications.

Goal:Develop the skills to design prompts that guide AI to produce desired outcomes.

Explore how generative AI can automate business processes and improve efficiency.

Goal:Apply generative AI to optimize and automate business workflows.

Learn how generative AI can be leveraged for innovative product design and development.

Goal:Use generative AI to enhance creativity and efficiency in product design.

Learn how to establish and apply evaluation metrics for assessing generative AI outputs.

Goal:Develop the ability to evaluate generative AI outputs using standardized metrics.

Engage with real-world case studies and hands-on exercises to apply generative AI concepts.

Goal:Apply learned concepts to practical scenarios through case studies and practice.

Learn how to utilize generative AI to streamline workflows and increase productivity.

Goal:Apply generative AI techniques to improve business workflows.

Master the skills of prompt engineering to guide AI outputs effectively across different business applications.

Goal:Develop proficiency in engineering prompts to optimize AI outputs.