The landscape of project management is being fundamentally reshaped by artificial intelligence. This "Mastering the Future: Cognitive Project Management in AI Training Course" is a cutting-edge program designed for professionals who need to navigate the unique challenges and opportunities of leading AI-powered projects. From understanding the nuances of machine learning lifecycles to leveraging AI tools for project automation and risk mitigation, this course will equip you with the advanced skills required to drive successful and impactful AI initiatives in any organization.

Over this intensive 10-day course, you will learn how to apply cognitive principles to project management, moving beyond traditional methodologies to embrace an adaptive, data-driven approach. You will gain a deep understanding of the AI development lifecycle, stakeholder management in an AI context, and the ethical considerations that are paramount to success. By the end of this program, you will not only be proficient in managing AI projects but will also be able to strategically integrate AI into your organization's project portfolio, positioning yourself as a visionary leader in this transformative field.

Duration: 10 days

Target Audience:

• Project Managers
• Product Managers
• Data Scientists
• AI/ML Engineers
• Business Leaders
• Technology Consultants
• Team Leads
• Scrum Masters
• Organizational Change Agents
• Anyone involved in AI development projects

Objectives:

• Understand the unique lifecycle of AI projects
• Differentiate between traditional and AI project management
• Learn to manage the iterative and experimental nature of AI
• Master techniques for data governance and project planning
• Use AI tools for project automation and forecasting
• Understand the ethical and bias considerations in AI projects
• Develop a roadmap for scaling AI initiatives
• Effectively communicate complex technical concepts to stakeholders
• Manage risks and uncertainties inherent in AI development
• Create a framework for measuring the success and ROI of AI projects

Course Modules:

Module 1: Introduction to AI Project Management

• The shift from traditional to cognitive project management
• The core principles of CPMAI
• Understanding the AI development lifecycle
• Key differences between managing software and AI projects
• The role of the AI Project Manager

Module 2: The AI Project Lifecycle

• From ideation to deployment
• Data collection and preparation
• Model development and training
• Validation and testing of AI models
• The continuous improvement loop

Module 3: Data Management for AI Projects

• The importance of data quality
• Data governance and security
• Sourcing and handling large datasets
• Data labeling and annotation strategies
• The ethical implications of data

Module 4: Agile and CPMAI

• Applying Agile principles to AI projects
• The iterative nature of model development
• The use of sprints and backlogs in an AI context
• Managing scope creep with data-driven insights
• Retrospectives and continuous learning

Module 5: Stakeholder Management in AI

• Identifying and engaging key stakeholders
• Communicating project progress effectively
• Managing expectations around model performance
• The role of explainable AI (XAI) in stakeholder communication
• Building trust and transparency

Module 6: Planning and Estimation

• The challenge of estimating in an AI project
• Using a phased approach to planning
• Risk management and mitigation strategies
• Budgeting for data, compute, and talent
• The importance of a flexible roadmap

Module 7: Leveraging AI for Project Management

• Using AI tools for scheduling and resource allocation
• Predicting project risks and delays with machine learning
• Automating reporting and status updates
• The role of natural language processing (NLP) in project communication
• The future of AI-powered project management

Module 8: Ethical AI and Bias Management

• Understanding bias in data and models
• The ethical considerations of AI development
• Techniques for mitigating bias
• Regulatory and compliance requirements
• Building a framework for responsible AI

Module 9: Model Deployment and Operations (MLOps)

• The importance of a robust MLOps pipeline
• Continuous integration and continuous delivery for AI
• Monitoring model performance in production
• Managing versioning and updates
• The role of the PM in the deployment process

Module 10: Measuring AI Project Success

• Defining success metrics beyond traditional KPIs
• Measuring business value and ROI
• The importance of user adoption metrics
• A/B testing and experimentation
• Creating a portfolio of AI projects

Module 11: Team Dynamics and Leadership

• Building a multi-disciplinary team
• The role of the Project Manager as a coach
• Fostering a culture of experimentation and psychological safety
• Managing conflict and collaboration
• Leading without authority

Module 12: Case Studies in CPMAI

• Analyzing successful and failed AI projects
• Lessons learned from real-world scenarios
• Identifying common pitfalls and how to avoid them
• Applying best practices to a case study
• Peer-to-peer discussion and analysis

Module 13: Scaling AI Initiatives

• The challenges of scaling from pilot to production
• Creating a blueprint for enterprise-wide adoption
• The role of governance and oversight
• Managing the portfolio of AI projects
• Strategic planning for future AI investments

Module 14: Risk and Uncertainty Management

• The unique risks of AI projects
• Techniques for identifying and assessing risks
• Creating a proactive risk mitigation plan
• Managing uncertainty in model performance
• Contingency planning

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.