-
-
- Sciences, Mathematics
and Biotechnology - Biology
- Chemistry and Physics
- Clinical Laboratory Science
- Health Advising
- Life Science Business and Biotechnology
- Mathematics and Statistics
- Online Sciences Courses
- See the full list
- Technology and
Information Management - Writing, Editing and
Technical Communication
- Transfer Credit
- Online Learning
- Events
- Career Services
- Custom Programs
- Sciences, Mathematics
-
-
-
- Academic Services
- Course and Program Information
- Student Aid
-
-
-
Berkeley Global
As the importance of Artificial Intelligence (AI) grows across industries, technology practitioners will need to have a firm grasp of the various stages of AI adoption. In this course, you will learn about the practical realization of AI applications, common challenges organizations face when implementing AI and ML systems, and explore methods that users and technology leaders can utilize to overcome common challenges and barriers.
By the end of this course, you will have knowledge of concrete actions technology leaders can take to promote effective AI adoption.
Lead Instructor: Alexander I. Iliev, Ph.D., earned his doctorate from the College of Engineering at the University of Miami (UM) in 2009. He holds two patents in the Digital Audio Watermarking and Data Enhancement fields. Dr. Iliev’s research interests are in the fields of Big Data analytics, signal processing, personalization using speech and image signals, AI, ML and data mining.
Expert Speaker: Michael Wu, Ph.D., is one of the world’s premier authorities on AI, ML, data science and behavioral economics. He’s currently the Chief AI Strategist at PROS, an AI-powered SaaS provider that helps companies monetize more efficiently in the digital economy. He’s been appointed as a Senior Research Fellow at the Ecole des Ponts Business School for his work in data science.
Prerequisites: No specific prerequisites or entrance requirements are needed to enroll. Before starting the course, we strongly recommend that you have viewed the recording of the free expert panel public event:
Latest Engineering Trends for Artificial Intelligence and Machine Learning
Course Outline
Expand or collapse section
Course Objectives
Upon completion of this seminar, you will:
- Understand common approaches to explaining AI to organizational stakeholders.
- Learn about the evolution of business intelligence into AI and why AI is so important in industry today.
- Differentiate between AI and Machine Learning.
- Define major types of AI applications in industry and how innovative companies use AI to be competitive.
- Describe the state of AI today, the stages of the AI adoption maturity curve and how we can drive mass AI adoption in an enterprise.
- Identify the key challenges companies must overcome to effectively utilize AI.
- Explain how effective design can help users build more trust with AI systems and how to build that trust.
Intended Audience
- Advanced users, engineers, researchers and professionals in the fields of applied Machine Learning and practical Artificial Intelligence
- Specialists who work with Big Data and want to go beyond standard Deep Learning methods to create the next generation of Machine Intelligence
Loading...
Sections
Fall enrollment opens on June 20!