PROJECT MANAGEMENT: FUNDAMENTALS, METHODS, AND FRAMEWORKS FOR PROJECT MANAGEMENT

Registration Deadline: February 8, 2027

The course covers the basic concepts of the main international project management methodologies; in particular, it draws on the PMI Institute standard and emerging practices in Lean and Agile project management, with a special focus on Kanban and Scrum.

The course emphasizes a practical approach, aimed at providing the tools necessary to effectively manage projects. The criteria for selecting the most appropriate methodological approach based on the project’s characteristics will be explained, integrating traditional predictive methodologies with iterative and adaptive ones.

In particular, we will take an in-depth look at the Kanban framework (a lean framework) and the Scrum framework (an agile framework).

Date

February 15, 16, and 17, 2027

Language

Italian

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Registration fee

Adherent Cetif

€950.00 + VAT*

Non-Adherent Cetif

€ 1100.00 + VAT*

*Quota per participant

Discounts and economic benefits

To whom it is addressed

Managers, professionals, and corporate personnel involved in planning, coordinating, or overseeing projects

Formative Objectives.

understand the principles and main methodologies of project management, including both traditional (predictive) approaches and Lean and Agile methodologies;
be familiar with the tools and techniques used for project planning, monitoring, and control, and understand their purposes, scope of application, and limitations;
critically evaluate which methodological approach is most appropriate given the characteristics of the project, thereby supporting decisions regarding the planning, execution, and monitoring of activities;
use appropriate technical terminology to interact effectively with project managers, stakeholders, and others involved in project management;
Apply project management methods, tools, and techniques to manage complex projects in a managerial context.

The format

Innovative and effective teaching techniques geared toward the transfer of knowledge and behavior through:

theoretical lectures
moments of consolidation and critical revision of content
Exercises and simulations
use case and benchmark

The Course will be held in. Dual Mode: the participant at the time of registration will be able to communicate the most convenient mode of fruition.

Course Schedule.

Understanding when and for which tasks to use AI.
Determine what to delegate, what to have AI handle, and what to keep under human supervision.
Define the problem, objective, and expected outcome.
Break down a complex task into steps.
Crafting effective requests by considering context, audience, constraints, format, and quality criteria.
Use examples and reference materials.
Move from a single prompt to a progressive dialogue.
Improve prompts and output through successive iterations.
Ask the AI to clarify any doubts, assumptions, and missing information.
Exercise

Treat AI output as a suggestion, not as a finished product.
Distinguish between facts, interpretations, inferences, and recommendations.
Evaluate relevance, accuracy, completeness, consistency, and verifiability.
Identify errors, omissions, implicit assumptions, and generic content.
Verify data, statements, and sources.
Recognize the biases that may influence the user.
Determine what to keep, review, revise, or discard.
Integrate the output with knowledge, experience, and professional context.
Adapt the content, language, and structure to the audience.
Avoid simply copying and pasting.
Use AI to generate objections, alternatives, and different points of view.
Take responsibility for the outcome and the final decision.
Exercise