AI Project Management from Coursera

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.

What's inside

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.

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Focuses on both the technical and human aspects of AI project management, which is essential for leading successful and sustainable AI solutions

Explores Agile methodologies and change management, which are essential for adapting to the dynamic nature of AI projects and ensuring successful outcomes

Examines the labor dynamics of AI adoption, which helps learners understand how to build inclusive and sustainable AI solutions that consider the impact on the workforce

Covers the entire lifecycle of AI project management, from resource planning to deployment, which is crucial for effectively managing and scaling AI projects in real-world environments

Addresses ethical challenges and mitigating biases in AI systems, which is increasingly important for responsible AI development and deployment in various industries and applications

Requires learners to balance scalability with budget constraints, which may necessitate familiarity with cost optimization strategies and resource allocation techniques in AI projects

Reviews summary

Managing ai projects at scale

According to learners, this course provides a strong foundation for managing AI projects, particularly focusing on practical application and real-world scenarios. Students appreciated the insights into risk mitigation and ethical considerations specific to AI. The modules on team management and the labor dynamics of AI were highlighted as particularly valuable and unique. While some noted the need for prior basic AI understanding, many found the content clear and well-structured, making complex topics accessible for project managers.

Content is organized logically and easy to follow.

"The course is logically structured, with each module building well on the previous one."

"I found the breakdown of the AI project lifecycle into distinct modules very helpful."

"The flow of the course made it easy to absorb the information and understand the process."

Covers unique aspects like labor dynamics & ethics.

"The sections on AI's impact on labor and building diverse teams were topics I hadn't seen covered elsewhere and found incredibly insightful."

"Understanding the ethical challenges and biases in AI from a PM standpoint was a key takeaway for me."

"The focus on the human aspects and labor dynamics of AI projects was a unique and valuable part of the course."

Provides a solid basis for AI project management.

"This course gave me a solid foundation in understanding the unique challenges and opportunities in managing AI projects."

"I feel much more confident approaching AI initiatives now that I have this foundational knowledge."

"It provided a great overview of the AI project lifecycle from a management perspective."

Focuses on real-world application and actionable insights.

"The case studies and examples were highly relevant and helped me apply the concepts learned to my own work."

"I can immediately use the strategies for risk mitigation and team collaboration discussed in this course."

"The course content is very practical and geared towards real-world AI project challenges."

Some prior AI understanding is beneficial.

"While it's a management course, having a basic understanding of AI concepts before starting would be helpful."

"Some technical terms were used assuming a level of familiarity I didn't quite have initially."

"It helps if you're not coming into this completely new to the world of artificial intelligence."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in AI Project Management with these activities:

Review Agile Methodologies

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Refresh your understanding of Agile methodologies to better grasp the project management strategies discussed in the course.

Browse courses on Agile Methodologies

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Read articles and blog posts about Agile project management.
Watch introductory videos on Agile frameworks like Scrum and Kanban.
Take a short online quiz to test your knowledge of Agile principles.

Review 'AI Superpowers: China, Silicon Valley, and the New World Order'

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Gain a broader understanding of the global AI landscape and its impact on labor and society.

View Putting Knowledge to Work on Amazon

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Read the book, focusing on chapters related to AI's impact on labor and the economy.
Take notes on key arguments and examples presented in the book.
Reflect on how the book's insights relate to the challenges of managing AI projects.

Review 'Competing in the Age of AI'

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Understand how AI is transforming business strategy and leadership.

View Competing in the Age of AI: Strategy and... on Amazon

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Read the book, focusing on chapters related to AI strategy and leadership.
Identify key concepts and frameworks presented in the book.
Reflect on how these concepts can be applied to AI project management.

Three other activities

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Create a Presentation on Ethical Considerations in AI Project Management

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Solidify your understanding of ethical challenges in AI by creating a presentation that explores potential biases and mitigation strategies.

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Research ethical frameworks and guidelines for AI development and deployment.
Identify potential biases in AI systems and their impact on different stakeholders.
Develop mitigation strategies to address biases and ensure fairness in AI projects.
Create a visually appealing presentation with clear and concise explanations.

Develop an AI Project Risk Assessment Template

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Apply risk mitigation strategies learned in the course by creating a practical risk assessment template for AI projects.

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Research common risks associated with AI projects (e.g., data bias, model drift, ethical concerns).
Design a template with categories for risk identification, assessment, and mitigation strategies.
Populate the template with specific examples relevant to different AI project types.
Share the template with peers for feedback and refinement.

Develop a Resource Allocation Plan for an AI Project

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Practice resource management skills by creating a detailed resource allocation plan for a hypothetical AI project.

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Define the scope and objectives of the AI project.
Identify the resources required for each phase of the project (e.g., personnel, software, hardware, data).
Estimate the cost and availability of each resource.
Create a resource allocation plan that optimizes resource utilization and minimizes costs.
Present the plan to peers for feedback and refinement.

Career center

Learners who complete AI Project Management will develop knowledge and skills that may be useful to these careers:

Project Manager

A project manager is responsible for the planning, execution, and closing of projects, and this course will be directly applicable to those who work on artificial intelligence projects. In this role, you will organize project teams, create timelines, and manage budgets. This course's focus on the entire lifecycle of AI project management, from resource planning to deployment, aligns seamlessly with the core responsibilities of a project manager. Furthermore, the course's emphasis on balancing scalability with budget constraints and mitigating risks will help advance a project manager's career. The material on team collaboration and conflict resolution are essential for overseeing teams.

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AI Program Manager

An AI program manager oversees multiple related AI projects, ensuring they align with organizational goals. A program manager ensures that each project contributes to the overall program's success. This course will be extremely helpful to those working as program managers in AI. The course provides a holistic view of the AI project lifecycle, covering resource planning, risk mitigation, and team collaboration. This course dives into the labor dynamics of AI adoption, and addresses the need for cognitively diverse teams which are essential considerations for a program manager. With the course's focus on scaling existing projects and implementing new ones, program managers are better equipped to manage complex initiatives.

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Technical Program Manager

A technical program manager oversees complex technical projects, ensuring they align with strategic organizational goals. The 'AI Project Management' course will be very helpful to a technical project manager because its emphasis on managing AI projects at scale is essential to this role. In this role, you need to be able to understand the technical details of a project, and how to manage a team to deliver a project on time and within budget. This course's focus on balancing scalability with budget constraints, mitigating biases, and promoting team collaboration will be very useful for you as a technical program manager. Also, the course's focus on risk mitigation and best practices will be directly applicable to your success.

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AI Product Manager

An AI product manager guides the strategy, roadmap, and execution of artificial intelligence products. This role requires a deep understanding of both the technical and business aspects of AI. The 'AI Project Management' course, with its focus on the entire project lifecycle, is ideal for a product manager looking to build intelligent solutions. In this role you must make decisions that impact a product's success and its ability to adapt to the market. This course will be useful because it addresses the management and ethical concerns that arise in AI. This course emphasizes balancing performance with ethical considerations and managing stakeholder engagement, skills which every product manager needs.

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AI Strategist

An artificial intelligence strategist develops and guides the implementation of AI strategies within an organization. This role requires a blend of technical knowledge with strategic insight. The 'AI Project Management' course is highly relevant to this role, as it focuses on the entire lifecycle of AI projects from planning to deployment, and strategic decision-making. The course examines the labor dynamics of AI adoption and strategies to create cognitively diverse teams, all aspects that are pertinent to an AI strategist. With the course's focus on balancing scalability, budget constraints, and ethical concerns, an AI strategist is better prepared to lead an organization's AI initiatives.

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Technology Consultant

A technology consultant advises organizations on how to use technology to meet their business goals. The 'AI Project Management' course will help a technology consultant who works with AI strategy, implementation, and management. This role requires you to understand the complexities of AI projects and how they fit into an organization's overall strategy. This course will be useful because of its focus on scaling AI projects, managing budgets, mitigating biases, and fostering team collaboration. The course teaches concepts that would be very helpful for advising clients on AI initiatives and deployments. By learning effective practices for optimizing performance and minimizing risks, a consultant will be able to help clients be successful in artificial intelligence.

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AI Team Lead

An AI team lead manages a team of AI specialists, guiding them to achieve project goals. The 'AI Project Management' course will help a team lead by providing the management skills necessary for this role. This role requires a blend of technical knowledge, team leadership, and project management abilities. The course's exploration of team collaboration, labor dynamics, and skill clustering would directly contribute to effective team management for an AI team lead. The course covers key management principles like balancing scalability with budget constraints, which are crucial for team leads who are responsible for delivering results.

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Data Science Manager

A data science manager leads a team of data scientists, overseeing projects that leverage data to drive business decisions. The 'AI Project Management' course may be particularly useful because of its focus on the practical aspects of managing AI projects and the labor dynamics involved. This role requires a blend of technical expertise and management skills, and this course provides the management tools needed to lead teams. The course covers topics such as balancing scalability with budget constraints and mitigating biases in AI systems, which would be very valuable for a data science manager. This course may help a data science manager who seeks to lead successful projects.

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Solutions Architect

A solutions architect designs and oversees the implementation of technological solutions to meet business needs. This role requires a deep understanding of technology and business strategy, and the 'AI Project Management' course will be helpful by covering the complexities of AI projects. In this role, you will need a solid understanding of the entire lifecycle of AI projects, and the course covers that. The course’s emphasis on scalability, resource management, and strategic decision-making will equip a solutions architect to design practical solutions. The course may be useful for a solutions architect who wishes to expand into the design and implementation of AI solutions.

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Agile Coach

An agile coach guides teams in adopting and implementing Agile methodologies, which are essential for effectively managing AI projects. The 'AI Project Management' course will be useful to an agile coach by providing insights into the specific challenges of AI project management. In this role, you will help teams improve their process, and this course's emphasis on Agile methodology, change management, and project optimization is helpful. The course also covers team collaboration and risk mitigation, which are also important aspects of an agile coach's role. This course may help an agile coach improve a team's success in AI projects.

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Digital Transformation Manager

A digital transformation manager leads an organization's efforts to integrate digital technology into all areas of business. This role requires an understanding of technology and change management, and this course may be useful by covering the project management of artificial intelligence. This course’s focus on the lifecycle of AI projects and the practical aspects of managing and scaling projects will be a helpful addition to a digital transformation manager's capabilities. The course covers key areas of AI project management, including resource planning and risk mitigation, which are essential for you to successfully oversee digital transformation. This course may help you learn to deploy technology successfully.

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Innovation Manager

An innovation manager is responsible for driving new ideas and technologies within an organization. The 'AI Project Management' course may be useful for an innovation manager by focusing on the practical aspects of bringing AI projects from concept to reality. Innovation managers will explore new technologies and how to implement them, and this course's focus on the entire AI project lifecycle, from planning to deployment, will be helpful in that endeavor. This course provides insight on balancing scalability with budget constraints which is important in the innovation process. Furthermore, its emphasis on mitigating biases and fostering team collaboration will be helpful for an innovation manager's role.

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Operations Manager

An operations manager oversees the daily functioning of an organization, ensuring processes are efficient. The 'AI Project Management' course may be useful for an operations manager because of its emphasis on effective practices for optimizing performance, minimizing risks, and addressing ethical challenges. The course's focus on scaling AI projects while managing budgets would directly apply to an operations manager's work. In operations, you will look for ways to improve existing processes, and this course could help you understand how to incorporate AI into these processes. This course covers the labor dynamics of AI adoption and strategies to create diverse teams, topics helpful for an operations manager.

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Business Analyst

A business analyst identifies business needs and helps translate them into actionable requirements for IT systems and projects. This 'AI Project Management' course will be useful for a business analyst working on AI projects, as it provides insight into the management and ethical challenges of AI. The course’s overview of the entire AI project lifecycle, from planning to deployment, is very useful to a business analyst. The course, with its focus on managing budgets and mitigating biases, will help a business analyst understand the considerations of AI implementation. This course may be useful for a business analyst who wishes to explore the world of AI.

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Change Management Specialist

A change management specialist helps teams navigate changes within an organization, including the adoption of new technologies. The 'AI Project Management' course may be useful as the course covers change management in the context of AI projects. Change management specialists need to understand organizational challenges and implement solutions, and this course can help in that endeavor. The course emphasizes team collaboration and change management, which are essential skills for this role. It also covers the labor dynamics of AI adoption and strategies for building diverse teams, which are helpful when implementing change.

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AI Project Management

What's inside

Syllabus

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Reviews summary

Managing ai projects at scale

Activities

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