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. Limoges onsite live AI Engineering trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Limoges, City Center
NobleProg Limoges, 50 Boulevard Gambetta, Limoges, France, 87000
The nearest airport to the training center: Limoges International Airport
Nearest train station: Limoges-Bénédictins train...
The nearest airport to the training center: Limoges International Airport
Nearest train station: Limoges-Bénédictins train station
Nearest parking lot to training center: Parking Place d'Aine
Nearby cafés, restaurants and bars: Restaurant ESCROCS, Restaurant Le Glacier, Bar Le Duc Etienne
Training can also be organized on your premises in Strasbourg or remotely. The 3rd option is to rent a room specifically for the duration of the course.
Training sessions can be given in English or French. For each session, we organize a coordination call with the trainer and participants to adapt the program to your expectations and level. Training includes theory, discussion, questions/answers and practical exercises.
Remote training is delivered via DaDesktop for training, a software package published by NobleProg that enables participants to have a workstation (VM) set up specifically for the training.
This instructor-led, live training in Limoges (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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