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. Yokohama onsite live AI Engineering trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
The centre is located within a 5-minute walk from JR Kannai station and a 3-minute walk from Yokohama Blue Line Subway’s Ka...
The centre is located within a 5-minute walk from JR Kannai station and a 3-minute walk from Yokohama Blue Line Subway’s Kannai station. On the north side of the centre is the traditional business district lined with governmental offices, including the prefectural office, Yokohama’s city hall, customs , and port authorities. The area is home to a large number of import / export companies. The city is known for its international air which attracts expats as well as the good old cultural heritage loved by tourists. Tourism thrives here, with many attractions, hotels near the waterfront and the retro downtown area of Motomachi. Yokohama station, one of the biggest hubs in the Tokyo metropolitan area is less than a 10 minute train-ride from this centre. Yokohama station connects to many railway companies and you will reach Tokyo or Shibuya station in 30 minutes.
This instructor-led, live training in Yokohama (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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