The course "AI Project Management" equips learners with the tools and strategies to successfully design, manage, and scale AI projects in real-world environments. Covering the entire lifecycle of AI project management, from resource planning to deployment, the course emphasizes effective practices for optimizing performance, minimizing risks, and addressing ethical challenges. Learners will explore key management principles, such as balancing scalability with budget constraints, mitigating biases in AI systems, and fostering team collaboration.
What makes this course unique is its focus on both the technical and human aspects of AI project management. By analyzing the labor dynamics of AI adoption and exploring strategies to create cognitively diverse teams, participants gain insights into building inclusive, sustainable AI solutions. Case studies and practical examples ensure that learners leave with actionable knowledge to lead AI initiatives confidently. Whether scaling existing projects or implementing new ones, this course provides the expertise to succeed in today's AI-driven landscape.
Overview
Syllabus
- Course Introduction
- This course explores the end-to-end process of managing at-scale AI projects, focusing on key stages, management concerns, and risk mitigation strategies. You will learn effective team management, addressing labor trends, skill clustering, and division of labor. This course emphasizes sound management practices to optimize AI delivery and team performance. You will also evaluate various assessment strategies to enhance project success.
- AI Impacts on Labor
- This module covers key labor-related topics in AI projects, including common roles and essential skills required for success. It explores which roles can or should be automated and examines the speed of labor transition in AI-driven environments. In this module, you will learn how to assess the performance of diverse skills and roles to maintain meritocracy and how to build cognitively diverse teams for optimal outcomes.
- Designing At-Scale AI Projects
- This module explores the complexities of designing and delivering scalable AI projects, covering the entire lifecycle from planning to deployment. It addresses technical and management aspects, focusing on scalability, resource management, and strategic decision-making. You will gain insights into managing AI projects and balancing performance with ethical and operational concerns. By the end, you will be equipped to design AI systems that meet both current and future demands, while managing budgets, risks, and stakeholder engagement.
- Managing At-Scale AI Projects
- In this module, you will gain insights into effective management strategies to optimize the delivery of AI projects on a large scale. Emphasizing risk mitigation and best practices, the module covers essential areas of AI project management, including Agile methodologies, change management, and sound management practices. By the end, you will be equipped to describe effective management solutions for AI projects and demonstrate robust management practices for successful outcomes.
Taught by
Ian McCulloh
