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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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The Training: Mastering Ultralytics and YOLO: From Installation to Creating Object Detection Models 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.
To ensure the quality of the Training: Mastering Ultralytics and YOLO: From Installation to Creating Object Detection Models training, Learni provides the following 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.
The assessment of skills acquired during the Training: Mastering Ultralytics and YOLO: From Installation to Creating Object Detection Models training is carried out through:
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Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Presentation of the YOLO family and the Ultralytics framework. Installation of the Python environment, GPU & CUDA, installation of the Ultralytics package, discovery of the API and main features. First detection tests with a pre-trained model on images and videos.
Compatible dataset formats (COCO, Pascal VOC, YOLO). Creating and annotating custom data (LabelImg, Roboflow). Using the YAML format to describe a dataset. Tips for managing large volumes of data. Practice on complete preparation of a client case study.
Training configuration: choice of architecture (YOLOv8, etc.), hyperparameter settings, use of cross-validation. Performance monitoring via integrated dashboards. Export and consumption of the model in different applications (web, edge, REST API). Tips for optimization, scalability, and production maintenance.
Target audience
Data professionals, Python developers, computer vision researchers wishing to leverage Ultralytics for object detection with YOLO.
Prerequisites
Basics in Python and Machine Learning; knowledge of deep learning recommended.
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