AI Leadership: A Three-Course Series
Artificial intelligence will have a profound impact on the way we work and on what shape our jobs and careers will take in years to come. In this three-course series, students will develop a deep and practical understanding of this new and transformative technology. They will explore the foundational underpinnings of AI and large language models, learn how to strategically select AI applications to meet specific business needs, and even have a chance to build their own AI-based solutions, with little or no coding needed. Students who complete the series will be able to seamlessly integrate AI into their own work processes and effectively lead AI initiatives within their organizations.
No prerequisites or prior experience with AI are required. Completing each course guarantees priority registration in the following quarter. Each course can be taken independently as well.
SERIES SCHEDULE
FALL 2024
Introducing AI Systems
This course examines well-known AI technologies such as natural language processing, computer vision, and pattern recognition. We will break each application down into its component parts to understand how the underlying technology works and why it's most appropriate for particular use cases. Developing this practical understanding of different AI models will enable students to strategically implement AI tools to increase productivity, reduce costs, or create new products and revenue streams.
Course Instructor
Gaurav Khanna
Senior Manager, Data Science and Digital Journeys, Cisco Systems
Gaurav Khanna has 25 years of experience in technology and entrepreneurship. During the past five years, he has led efforts to automate business workflows using machine learning and deep learning techniques. His work focuses on using large language models and generative AI to transform how users interact with sales acceleration platforms. Khanna is passionate about demystifying complex subjects and is a frequent speaker on AI/ML topics. He received a BS in physics from Yale and an MS and a PhD in materials science and engineering from Stanford.
This course has been completed.
WINTER 2025
Leading AI Transformation
This course offers frameworks and strategies for developing and implementing AI initiatives within organizations. Students will learn to identify high-impact AI use cases and align them with strategic business objectives. They will design a roadmap and requirements for bringing to life an AI solution, with particular emphasis placed on developing an AI vision, establishing an AI operating model, and fostering an AI-driven culture.
Course Instructor
Gauthier Vasseur
Business Analytics Leader and Strategist
Gauthier Vasseur has worked in business analytics and AI for large organizations such as Oracle, Google, and many data tech startups, helping global customers from a range of industries harness their data to improve their businesses. He is the executive director of UC Berkeley's Fisher Center for Business Analytics and co-founder of the Alliance for Inclusive AI. He focuses on driving awareness, education, and diversity in analytics. Vasseur received an MBA from l'École des Hautes Études (EDHEC) in France.
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SPRING 2025
Building and Scaling AI Solutions
This course provides students with practical skills for developing, deploying, and scaling AI solutions. Students will gain hands-on experience working across the entire AI application lifecycle—from data processing and model training to deployment, monitoring, and optimization. They will also have the opportunity to experiment with low-code/no-code approaches to conceptualizing and building AI-based applications.
Course Instructor
Hamza Farooq
Adjunct Professor, University of Minnesota and Santa Clara University
Hamza Farooq has over 15 years of experience leading data science and machine learning teams. His areas of expertise are experiment design, NLP, recommender systems, and time series forecasting. He was a senior research science manager at Google. Farooq received an MBA from Lahore University; an MS in business analytics and machine learning from the Carlson School of Management, University of Minnesota; and a BS in computer science from the National University of Computer and Emerging Sciences, Pakistan.