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. Onsite live AI Engineering training can be carried out locally on customer premises in Brighton or in NobleProg corporate training centers in Brighton.
NobleProg -- Your Local Training Provider
Brighton
3rd Floor, Queensberry House , Brighton, united kingdom, BN1 3XF
This centre occupies a prominent location on Queens Road which links Brighton station to the Churchill Square shopping cen...
This centre occupies a prominent location on Queens Road which links Brighton station to the Churchill Square shopping centre and the seafront. Queensberry House, which offers some sea views, is in the heart of the business district in this city. Brighton is a highly sophisticated and modern resort with a thriving economy and tourist industry. Millions of visitors flock here every year, both for leisure and to attend conferences and exhibitions at the Brighton Centre, one of the largest multi-purpose conference and exhibition centres in the country. Because it is home to so many businesses involved in media, particularly digital or 'new media', Brighton is sometimes referred to as 'Silicon Beach'. The city's priority sectors, which include financial services, creative industries and environmental technologies as well as digital media, are all growing steadily.
This instructor-led, live training in Brighton (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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