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Project Management

AI Project Management

Published by O'Reilly Media, Inc.

Intermediate content levelIntermediate

Managing and delivering AI projects

  • Learn the fundamentals of AI projects and their typical stages
  • Understand product ownership
  • Explore the roles and responsibilities of project members

Companies are adopting AI at a rapid pace and are looking for people able to manage and deliver their projects. But the changing and complex nature of AI implementation creates specific demands on project management, and, so far, no standardized practices have been established to govern the process. Success often depends on the quality of tactical AI management work.

Join expert Adrian Gonzalez-Sanchez to accelerate your learning curve toward competence and confidence in data and AI project management based on agile-hybrid methodologies and lessons learned from industry experience. You’ll get guidelines and practices that can help you tackle challenges involved in managing implementations of this fast-moving technology—learning the phases specific to AI projects, the roles and responsibilities of the AI project manager, and the methodology, interpersonal interactions, planning, and estimations that differ from traditional PM processes.

What you’ll learn and how you can apply it

  • Apply project management techniques specific to data and AI projects
  • Adapt the principles of agile and hybrid project management to AI-specific projects
  • Predict the necessary steps for a successful AI project and manage interactions with the data team

This live event is for you because...

  • You want to become a full stack AI project manager with hybrid knowledge to design, plan, implement and deliver successful AI projects.
  • You’re a software developer, ML engineer, or other technical professional who’s tasked with managing your own projects.
  • You work with both technical and business stakeholders, internal and external clients.

Prerequisites

  • Basic project management knowledge, including waterfall and agile methodologies
  • An understanding of AI fundamentals
  • General knowledge of AI-related tools, including cloud computing (useful but not required)

Recommended preparation:

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

AI project phases (60 minutes)

  • Presentation: The AI project lifecycle from a technical and project management perspective; the art of ideating, evaluating, and choosing good projects; the period between the project decision and the project kickoff; making the most of project prep and obtaining executive sponsorship and project resources; maintaining the balance between experimentation and implementation during execution; methodology for properly delivering the project outcome and transferring knowledge; toolkit with frameworks, reusable assets, etc.
  • Q&A
  • Break

Roles and responsibilities of an AI project manager (60 minutes)

  • Presentation: Roles of project manager, product owner, and others; approach, methodologies, and tools; types of meetings and goals; guidance for AI project managers to become great resources
  • Group discussion: Your idea of required skills for AI project management
  • Q&A
  • Break

An applied, illustrative case study (60 minutes)

  • Hands-on exercises: Use an illustrative AI project example to analyze implementation options; create an AI project road map
  • Group discussion: Phases, estimations, roles, responsibilities, and challenges of AI project management
  • Q&A

Your Instructor

  • Adrián González Sánchez

    Adrian Gonzalez Sanchez is a lecturer at Executive Education HEC Montréal and Concordia University Continuing Education. He also collaborates with Udacity and GetSmarter for MIT’s Sloan School of Management as a tutor and learning facilitator for executive AI and blockchain executive programs. A former practitioner with data-driven product companies in Europe and Latin America, his areas of expertise include management of complex technology projects, Big Data systems, data & AI corporate strategy, business-oriented Blockchain applications, cloud computing, telecommunications (4G/5G), and the internet of things. Mindful of the ethical and legal impact of technological innovation, Adrian’s a member of the Spanish Observatory for Social and Ethical Impact of Artificial Intelligence and is part of the end user community of the Cloud Native Computing Foundation (CNCF).

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