Course in Artificial Intelligence Applyed to Project Management

Learn how to integrate Artificial Intelligence throughout the life cycle of a project and improve productivity in Project Management.

Nid: 28093
Syllabus
Syllabus

1. Fundamental concepts of Artificial Intelligence and application in the company

  • General introduction to AI, history, and evolution
  • Main AI concepts and terminology
  • Differences between machine learning, deep learning and other branches of AI
  • Introduction to AI models and their general applications
  • AI work environment: core tools, languages, and platforms
  • Practical application cases

2. Advanced AI for project planning and management

  • Planning optimization: AI for resource, time, and task allocation
    • Optimization algorithms in project planning
    • Using AI to estimate schedules more accurately
  • Optimization in resource allocation: use of predictive algorithms for optimal resource allocation
  • Time and cost forecasting: regression models and predictive analytics in project planning
  • Task rescheduling: AI to automatically reschedule tasks based on delays and changes in resource availability
  • Limits of the application of AI

3. Predictive analytics and risk management with AI

  • Risk identification using AI: using machine learning to analyze historical project data and predict potential risks
    • Supervised vs. unsupervised models for risk identification
  • Predictive models applied to risk management: decision trees, neural networks for real-time risk assessment
  • Scenario analysis and simulations: using AI to create simulations of the impact of potential risks
  • Risk management automation: implementation of alerts and automatic notifications of potential risks

4. AI-supported project deshboarding and control

  • Real-time monitoring with AI: use of intelligent dashboards/personal assistants to track KPIs and project status
    • Data analysis for the control of progress, costs and resources
  • Early detection of deviations: AI to identify behavioural patterns that predict deviations from planning
  • Intelligent alerts and automated reporting: configuring systems that send automatic alerts when anomalies are detected in the project
  • AI system for project analysis. Options for project analysis from an AI-based system