Expert Seminar Series: AI and Machine Learning for Engineering

As a technology leader working on Human-Computer Interaction (HCI), Deep Learning (DL) and Artificial Intelligence (AI) related applications, you might be under constant pressure to stay one step ahead of your competitors in developing the latest analytic innovations. In order to achieve fair, impactful and sustainable AI and Machine Learning (ML) solutions, technology leaders need targeted insights into bias and equity, human-centered solutions and adapting AI for industry. Staying up to date on these latest trends will help you find the crucial balance between technology adoption, cultural change and a learned grasp of the new normal.

In this series, expert instructors explore how to effectively productize AI and ML applications, while sharing their own real-world experiences and solutions.

As a participant in this fully online, asynchronous program, you will gain real-world skills so that you can:

• Effectively operate and deploy AI and ML applications on a realistic and practical level.
• Understand the adoption of AI, AI maturity in the industry and many of the challenges faced along the way.
• Build human-centric ML solutions, with an emphasis on what would happen when data fails us.
• Measure biases in various AI and ML applications.

Start by watching the video “Latest Engineering Trends for Artificial Intelligence and Machine Learning,” where you will meet your instructors for this seminar series:

• Alexander I. Iliev, Lead Instructor, UC Berkeley Extension; Professor and Academic Head at SRH Berlin University of Applied Sciences
• Ali Rebaie, Data Anthropologist, President at Rebaie Analytics Group
• Nashlie H. Sephus, Tech Evangelist at Amazon AI, Founder of TheBeanPath.org
• Michael Wu, Chief AI Strategist at PROS

Next step: Dig deeper by enrolling in each 2-hour online Core Course.

"Technology leaders are under constant pressure to stay one step ahead of their competitors in developing the latest analytic innovations. However, to achieve fair and impactful sustainability, reality dictates that the undertaking of AI and Machine Learning (ML) will require a measured balance between technology adoption, cultural change, and a learned grasp of the new normal.

"The Expert Seminar Series in AI and Machine Learning for Engineering aims to explain some of the hot topics in the field, while giving technology leaders the knowledge they need to navigate through it."