Online or onsite, instructor-led live Prompt Engineering training courses demonstrate through interactive hands-on practice how to use cutting-edge tools and techniques in prompt engineering to generate impressive and realistic text and images.
Prompt 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 Prompt Engineering trainings in Graz can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
NobleProg Graz
Waagner-Biro-Strasse 47, Graz, Austria, 8020
Overview
Our training facilities are located at Waagner-Biro-Strasse 47 in Graz. Our spac...
Overview
Our training facilities are located at Waagner-Biro-Strasse 47 in Graz. Our spacious training rooms are located directly in the old town and offer optimal training conditions for your needs.
Directions
The NobleProg training facilities are best reached via the A9 motorway and the federal highway 67.
Parking spaces
There are parking spaces in the streets around our training rooms as well as the ContiPark multi-storey car park.
Local infrastructure
There are numerous restaurants in the downtown area and hotels are also within walking distance.
This instructor-led, live training in Graz (online or onsite) is aimed at AI practitioners and enthusiasts who wish to harness the power of prompts to generate impressive and realistic text and images.
By the end of this training, participants will be able to:
Have a solid understanding of prompt engineering concepts.
Write accurate and effective prompts for ChatGPT, Stable Diffusion, DALL-E 2, Leonardo AI, and MidJourney.
Generate hyper-realistic text and images using the latest tools and techniques in prompt engineering.
Use AI-powered prompt engineering tools to automate prompt generation.
Apply prompt engineering to various use cases.
Incorporate prompt engineering into their own projects and workflows.
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