Project Planning and Requirements Gathering
In this subheading, students learn how to effectively plan and scope AI projects. They explore techniques for gathering requirements, defining project objectives, and identifying success metrics. Students gain insights into the challenges associated with scoping AI projects, including data availability, resource constraints, and technological feasibility. They also learn how to create realistic project timelines and allocate resources efficiently.
Risk Management in AI Projects
Risk management is crucial in AI projects, as it involves handling uncertainties and mitigating potential challenges. In this subheading, students explore techniques for identifying, analyzing, and managing risks specific to AI projects. They learn about strategies for data quality assessment, model validation, and performance monitoring. Students also discuss ethical and legal risks associated with AI, including data privacy breaches and algorithmic bias.
Team Collaboration and Communication
In this subheading, students explore the importance of effective team collaboration and communication in AI projects. They learn about agile project management methodologies, such as scrum and Kanban, that facilitate iterative development and continuous improvement. Students gain insights into techniques for fostering cross-functional collaboration, managing stakeholder expectations, and ensuring clear communication within project teams. They also discuss the role of project managers in facilitating collaboration and resolving conflicts.
