Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training NavMesh - Optimizing AI Navigation in Unity training are: Mastery of Unity, C#, and basics of pathfinding in 3D environments. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training NavMesh - Optimizing AI Navigation in Unity training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training NavMesh - Optimizing AI Navigation in… | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Training NavMesh - Optimizing AI Navigation in Unity training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Training NavMesh - Optimizing AI Navigation in Unity training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training NavMesh - Optimizing AI Navigation in Unity training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training access terms and deadlines

Training objectives

Master NavMesh generation for complex professional environments

Develop autonomous AI agents with professional NavMeshAgent

Implement dynamic and reactive pathfinding in professional games

Optimize NavMesh performance for scalable projects

Design multi-agent navigation systems in teams

Deploy advanced NavMesh integrated into realistic simulations

Training program

Module 1NavMesh Fundamentals: Generation and Baking of Environments (Unity NavMesh Surface, Navigation Window)

In-depth discovery of Unity tools for creating navigation meshes, precise configuration of NavMesh surfaces with static and dynamic obstacles, optimized baking of complex environments such as urban or forest game levels, practical exercises on a company red-thread project, immediate validity tests and real-time adjustments for smooth AI from day one.

Module 2NavMeshAgent: Configuration and Basic Behaviors (speed, rotation, stopping distance)

Setup of intelligent AI agents via NavMeshAgent, advanced parameterization of properties for realistic 3D movements, implementation of C# scripts to follow dynamic targets, concrete cases of searches or patrols in procedural levels, interactive debugging with Unity visualizer, production of functional prototypes ready for team integration.

Module 3Advanced NavMesh Pathfinding: Dynamic Obstacles and Avoidance (OffMeshLink, NavMeshModifier)

Runtime change management with NavMeshObstacle and volumetric modifiers, creation of OffMeshLink for jumps or climbs, development of multi-agent avoidance systems in dense crowds, exercises on combat or escape scenarios, optimization of recalculations for 60 FPS smoothness, deliverables including a reusable module for your professional projects.

Module 4NavMesh Optimization: Performance and Multithreading (Async Baking, Agent Pooling)

Optimization techniques for large open worlds with asynchronous baking and mesh hierarchy, implementation of pooling for hundreds of agents without lag, Unity profiling to identify bottlenecks, case studies on AAA games like those from Ubisoft, refactoring exercises on an existing level, measurable results in CPU reduction up to 50% for scalable production.

Module 5NavMesh Integration in Complex Projects: Best Practices and Deployment (NavMeshLink, Custom Areas)

Synthesis with custom areas and traversal costs for strategic AI, integration with game systems like FSM or BT, development of a complete red-thread project with multiplayer sync, code review by the expert trainer, preparation for deployment on target platforms, delivery of certified templates and roadmap for sustainable professional skills.