Online or onsite, instructor-led live Predictive AI training courses demonstrate through interactive hands-on practice the fundamentals and advanced topics of Predictive AI.
Predictive AI 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 Predictive AI trainings in Stockholm can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Stockholm, Hötorget
NobleProg classroom in Scandic Klara Hotel Stockholm, Slöjdgatan 7, Stockholm, sweden, 111 57
Near Hötorget and the nearest station is Hötorget. It is right in the heart of shopping street. With 200 meters (5 minutes ...
Near Hötorget and the nearest station is Hötorget. It is right in the heart of shopping street. With 200 meters (5 minutes walk) to the T-Centralen metro station, it is super easy to get around Stockholm, and 800 meters to the Arlanda Express makes it convenient to get to the airport. The location offers a welcoming and professional atmosphere. It is also conveniently close (15 minutes walk) to the Royal Palace for those who want to take in the major sights.
This instructor-led, live training in Stockholm (online or onsite) is aimed at beginner-level IT professionals who wish to grasp the fundamentals of Predictive AI.By the end of this training, participants will be able to:
Understand the core concepts of Predictive AI and its applications.
Collect, clean, and preprocess data for predictive analysis.
Explore and visualize data to uncover insights.
Build basic statistical models to make predictions.
Evaluate the performance of predictive models.
Apply Predictive AI concepts to real-world scenarios.
This instructor-led, live training in Stockholm (online or onsite) is aimed at intermediate-level DevOps professionals who wish to integrate predictive AI into their DevOps practices.By the end of this training, participants will be able to:
Implement predictive analytics models to forecast and solve challenges in the DevOps pipeline.
Utilize AI-driven tools for enhanced monitoring and operations.
Apply machine learning techniques to improve software delivery workflows.
Design AI strategies for proactive issue resolution and optimization.
Navigate the ethical considerations of using AI in DevOps.
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