Online or onsite, instructor-led live AI Engineering training courses demonstrate through interactive hands-on practice how to apply artificial intelligence techniques to solve complex problems in various domains.
AI Engineering training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Toulouse onsite live AI Engineering trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Toulouse, City Center
Mutliburo Toulouse, 9 Rue de Sébastopol, Toulouse, france, 31000
The business center is located in the Compans business district on the edge of Compans Caffarelli Park, which extends over...
The business center is located in the Compans business district on the edge of Compans Caffarelli Park, which extends over 10 hectares.
Many businesses have settled in this area, attracted both by the situation between the historic heart and the ring road that leads to the airport and the modernity of the site. Note the proximity of the conference center of Toulouse.
The business center offers its fully equipped offices and 2 meeting rooms to organize trainings and business meetings. All rooms are air-conditioned. Your visitors will be welcomed by our teams who will organize your day (preparation of rooms, internet connections, coffee break, catering, secretarial, hotel booking
This instructor-led, live training in Toulouse (online or onsite) is aimed at beginner-level to intermediate-level AI engineers and software developers who wish to gain a foundational understanding of AI engineering principles and practices.By the end of this training, participants will be able to:
Understand the core concepts and technologies behind AI and machine learning.
Implement basic machine learning models using TensorFlow and PyTorch.
Apply AI techniques to solve practical problems in software development.
Manage and maintain AI projects using best practices in AI engineering.
Recognize the ethical implications and responsibilities involved in developing AI systems.
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