AI academy: Time Management and Learning by Experience

This 1-day workshop equips learners with a practical toolkit that links time management with experiential learning loops to improve execution over time. Participants learn how to size work, manage dependencies and protect focus, then use after-action reviews and reflection-to-action routines to continuously improve how they plan, deliver and adapt. The session is built on a recurring learning loop: concise concepts, hands-on experimentation and structured peer sharing, using scenarios aligned with DLH Academies contexts (AI/Cyber/Quantum learning environment).

- Inclusion: align expectations, working agreements and success criteria for the day

- Core concepts: key models, checklists and common pitfalls

- Guided experiments: scenarios, role-plays or tool-driven exercises (progressive difficulty)

- Peer exchange: structured sharing, peer coaching and practical feedback

- Action planning: personal next steps and transfer-to-practice commitments

By the end of this training, participants will be able to:

• Explain the key concepts and vocabulary related to the topic
• Apply at least two practical tools or frameworks during exercises
• Receive peer feedback and refine an approach suited to their context
• Develop a clear, actionable plan to implement within the next 2–4 weeks

Active, learner-centered facilitation combining short inputs, guided practice, group debriefs and peer exchange. The trainer uses timeboxing, micro-feedback loops and real-life scenarios to maximize transfer to practice.