When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
AI Project Management
This AI Project Management training course teaches professionals how to expertly manage the unique challenges and opportunities of AI projects. Participants gain a deep understanding of the AI...
Read MoreThis AI Project Management training course teaches professionals how to expertly manage the unique challenges and opportunities of AI projects. Participants gain a deep understanding of the AI project lifecycle and learn to define clear roles and responsibilities, effectively mitigate AI-specific risks, engage stakeholders throughout the project, and implement strategies for continuous improvement. By the end of this course, attendees are prepared to successfully lead AI projects.
Skills Gained
- Master the AI project lifecycle, from conception to deployment, enabling successful project planning, execution, and oversight
- Develop robust risk management strategies and stakeholder engagement plans to address challenges and ensure project success
- Optimize resource allocation, manage technical and human resources effectively, and foster seamless collaboration across project roles
- Implement effective change management practices, including communication strategies, to overcome resistance and cultivate a culture of continuous learning
Prerequisites
This course is designed for project managers specializing in AI projects, data scientists and AI engineers transitioning into project management roles, and business leaders overseeing AI initiatives. Attendees must have:
- Experience with technology project management and delivery
- Experience in project management or leadership roles
- Familiarity with AI and machine learning pipelines is recommended but not required
Course Details
Outline
The AI Project Lifecycle
- Understand AI project phases
- Identify AI business opportunities
- Ideation: Identifying business problems
- Data Collection & Preparation: Data requirements and quality
- Model Selection & Training: Choosing and training AI models
- Evaluation & Refinement: Model performance and bias detection
- Deployment & Maintenance: Integrating AI models into production
Project Scoping and Management
- Develop comprehensive AI project plans
- Align AI projects with business objectives
- Defining Project Goals: Setting SMART goals
- Identifying Resources: Estimating technical and human resources
- Developing a Project Plan: Timelines and management
- Project Management Tools & Techniques: Agile, Waterfall methodologies
AI Project Roles and Responsibilities
- Define roles within an AI project team
- Understand the responsibilities of each role
- Executive Sponsor: Project champion and leader role
- Project Manager: Team leadership and resource management
- Data Scientist: Data preparation and model development
- AI Engineer: Model deployment and scalability
- Domain Expert: Business context and solution evaluation
Risk Management in AI Projects
- Identify potential risks in AI projects
- Develop risk mitigation strategies
- Risk Identification: Common AI project risks
- Mitigation Strategies: Techniques to address risks
- Contingency Planning: Preparing for unforeseen issues
Stakeholder Engagement and Change Management
- Engage and manage project stakeholders
- Develop effective communication strategies
- Identifying Stakeholders: Mapping stakeholders and their interests
- Communication Strategy: Plans for stakeholder engagement
- Managing Expectations: Techniques for effective communication
- Change Management: Addressing resistance and fostering learning
AI Solution Delivery and Continuous Improvement
- Deploy AI models effectively
- Establish robust monitoring and governance frameworks
- Model Deployment Strategies: On-premise, cloud, hybrid
- Monitoring and Logging: Tracking performance and security
- Governance and Explainability: Responsible AI practices
- Continuous Improvement: Feedback loops for refinement
Conclusion