Online or onsite, instructor-led live Qwen training courses demonstrate through interactive hands-on practice how to use Qwen's large language models (LLMs) to generate human-like text, automate content creation, and enhance natural language processing applications.
Qwen 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 Qwen training can be carried out locally on customer premises in Östergötland or in NobleProg corporate training centers in Östergötland.
NobleProg -- Your Local Training Provider
Linköping
NobleProg classroom in Scandic Linköping, Gamla Tanneforsvägen 51, Linköping, sweden, 582 54
Scandic Linköping City is a modern conference place. It's located in central Linköping and also close to Linkoping Cathedral and Linköping Garden Society. Linköping Airport is just a 5-minute car drive away from the conference centre. Other famous landmarks such as the Swedish Airforce Museum and the Old Town is only a 10-minute drive as well.
This instructor-led, live training in Östergötland (online or onsite) is aimed at advanced-level AI developers and enterprise architects who wish to customize and deploy Qwen for various enterprise applications.
By the end of this training, participants will be able to:
Customize Qwen to meet specific enterprise needs.
Deploy Qwen in a cloud or on-premise environment.
Integrate Qwen with existing enterprise systems and applications.
Monitor and optimize the performance of Qwen-based solutions.
This instructor-led, live training in Östergötland (online or onsite) is aimed at advanced-level NLP specialists, data scientists, and AI researchers who wish to integrate Qwen into their NLP workflows.
By the end of this training, participants will be able to:
Understand the architecture and features of Qwen.
Utilize Qwen for advanced NLP tasks, including text generation, analysis, and transformation.
Integrate Qwen into AI applications for processing natural language data.
Optimize NLP workflows using Qwen APIs and libraries.
Evaluate and fine-tune Qwen models for specific tasks.
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