Devconf.US

Angela Andrews

Angela Andrews is a senior solution architect as well as co-host for Compiler, a Red Hat podcast where they go beyond the buzzwords and jargon to simplify tech topics. She joined Red Hat in 2020 and before that, she spent the past 15 years working as a systems administrator in higher education supporting Windows, Linux, virtualization, storage and automation. In her free time she likes to read, workout and play with her dog, Scout.


Session

08-14
15:20
35min
AI & Automation: How Generative AI and Automation Can Revolutionize Certification Study
Randy Romero, Angela Andrews, Jordan Jacobs, Kush Gupta

In the fast-paced world of technology, staying ahead of the curve is crucial. Acquiring technical certifications has become the cornerstone of professional development, but the journey from aspirant to certified expert is a challenging one. This panel discussion, "AI & Automation: How Generative AI and Automation Can Revolutionize Certification Study" delves deep into the multifaceted process of preparing for and passing technical certification exams using AI and automation.

The panel will take you through their usage of AI, automation,time management process, study tips and what it takes to pass. With experienced test takers who have AWS, Azure, Red Hat, and others exams under their belts, they’ll share their rules for success and open your aperture to the benefits of using an emerging technology like generative AI as well as using automation to fast track your task-based study in a repeatable way.

Whether you are a newcomer to the certification world or a seasoned professional looking to upskill, our panel of experts will provide valuable insights and practical advice. Join us for a thought-provoking discussion that will empower you to tackle technical certification exams with confidence and success. "AI & Automation: How Generative AI and Automation Can Revolutionize Certification Study" is your roadmap to conquering the world of technology certifications.

Artificial Intelligence and Data Science
Conference Auditorium (capacity 260)