Course 1 is your foundation: what “project design” really means, how grant writing has evolved into strategic leadership, and how to define a fundable research project. You’ll classify project types, map the project lifecycle, and learn where AI helps (structure, drafts, consistency) vs. where humans must lead (innovation, partners, decisions). You finish with a crisp problem–solution statement and a checklist for the pages ahead. Includes quick AI exercises to lock in novelty, goals, and scope.

Course 2 turns an idea into a fundable strategy. You’ll apply a structured project design framework, align with calls and stakeholder needs, and set up the core proposal components with the right AI–human split. We’ll sharpen objectives using SMART, frame maturity with TRL, and craft a defensible innovation narrative. You’ll leave with a validated value proposition, scoped approach, and ready-to-write outline for the proposal core. Includes examples of stronger wording and prompts you can reuse.

Course 3 is about making evaluators believe your project matters. You’ll connect concept and methodology into one coherent logic, show ambition beyond the state of the art without hype, and design impact from day one across academic, economic, and societal dimensions. You’ll learn how to benchmark, justify choices, and communicate advantage with evidence and key metrics—so the project reads as bold, credible, and worth funding. Includes impact statements, metrics, and reviewer-friendly phrasing.

Course 4 focuses on execution credibility: how your project will actually run. You’ll translate objectives into work packages, deliverables, and timelines with dependencies, then present governance evaluators trust (steering, WP leads, reporting, decisions). We’ll build a risk system with owners, triggers, mitigations, and monitoring. Includes adaptable WP, governance, and risk-table templates. Link risks and costs to WPs and milestones. Add PERT/Gantt logic and a simple delay-contingency plans.

Course 5 covers the final win factors: budget logic, evaluator psychology, and a repeatable AI workflow. You’ll build a budget that matches work packages and proves feasibility, write with maximum clarity and skimmability, and set rules for AI use. We’ll turn human–AI collaboration into a simple process you can reuse for every submission, and you’ll finish with a final alignment checklist that catches weak links before submission. Includes a budget sanity check and a submission-ready QA routine.

Learn how ChatGPT processes queries, how memory and training settings affect confidentiality, and how to set up a safe, high-performance workflow. Includes a one-page setup checklist, Green/Amber/Red input rules, prompt templates, and a two-lane method (public desk research vs confidential drafting) to boost proposal quality without leaking sensitive consortium data.

A practical module on lump-sum funding — now around half of Horizon Europe 2026-27 call topics. How lump-sum changes budgeting and work-package design, how completion-triggered payment works, and how to build a budget the Commission will accept. 7 lessons plus a downloadable budget & work-package checklist. Proposal guidance, not legal or audit advice — always verify call-specific rules on the Funding & Tenders Portal.