Applications of Artificial Intelligence in Project Management

$3500.00

vuneu

Introduction to Artificial Intelligence: Definition of Artificial Intelligence, its types, and applications.
Project management concepts: Definition of project management, roles and responsibilities of the project manager.
Integrating artificial intelligence in project management: How can artificial intelligence improve the effectiveness of project management?
Practical examples: Case studies from different industries.

Data analysis using artificial intelligence: How to collect and analyze data using artificial intelligence techniques to support decision-making.
AI tools in scheduling and planning: Tools like predictive models to forecast project timelines.
Predictive simulation: Using artificial intelligence to simulate different outcomes in project planning.
Practical exercise: Using one of the smart tools to create a project plan.

Risk analysis: Using artificial intelligence to identify potential risks in the project.
AI models for risk assessment: Applications such as machine learning for risk prediction.
Automated risk management: Tools that help mitigate risks through artificial intelligence.
Practical exercise: Project risk analysis using an artificial intelligence tool.

Project progress monitoring: How to use artificial intelligence to monitor project progress in real-time.
Machine learning for performance improvement: How machine learning techniques help enhance productivity.
Team management using artificial intelligence: improving communication and task allocation using smart tools.
Practical exercise: Preparing a project progress monitoring report using artificial intelligence tools.

AI-supported decision-making: Using artificial intelligence to support strategic decisions.
Communication with teams using artificial intelligence: Using smart tools to improve collaboration between work teams.
AI tools for leadership: Analyzing how AI can support project leaders in decision-making.
Practical exercise: Using AI tools to support a critical decision in a project.

The theoretical content: It is delivered through interactive lectures and explanation of basic concepts.
Practical content: It is conducted through practical applications, case studies, and group exercises using the available tools.
Interaction and discussions: Workshops and discussion sessions to exchange experiences and ideas among participants.
Educational materials: Interactive educational materials including videos, presentations, and real-life examples from companies.

Project managers and supervisors.
Project teams.
Those interested in applying artificial intelligence technologies in various fields.