Online or onsite, instructor-led live Ollama training courses demonstrate through interactive hands-on practice how to use Ollama to run, fine-tune, and deploy local AI models efficiently.
Ollama 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 Ollama trainings in Berlin can be carried out locally on customer premises or in NobleProg corporate training centers.
Our training facilities are located at Brückenstr. 4 in Berlin. Located on the fourth floor of a well-kept office building, our premises offer enough space for successful training courses in the heart of Berlin, within walking distance of the Jannowitzbrücke station.
Directions
The NobleProg training facilities are located in the heart of Berlin's Mitte district, just one underground station from Alexanderplatz, one of the centres of this vibrant city. By public transport you can reach us either by underground line U8 to Jannowitzbrücke station, followed by about 100 meters on foot.
Parking
Cars can be parked in the area along Brückenstr. and the nearby side streets, even if you may have to search for a moment. There is no charge for parking.
Local Amenities
Around the Rosenthaler Platz there are numerous small restaurants and shops where you can eat well and cheaply. There are also some hotels close by if you need accommodation for the training.
Our training facilities are located at Dianastrasse 46 in Potsdam-Babelsberg.
Our spacious training rooms are located directly opposite the Filmstudios Babelsberg and offer optimal training conditions for your needs.
Arrival
The NobleProg training facilities are conveniently located near the Medienstadt Babelsberg railway station,
and the A115 motorway is also easily accessible.
Parking
Parking is available in the surrounding streets around our training rooms.
Local Services
Potsdam offers numerous hotels and restaurants and is easily accessible thanks to its well-developed public transport system.
This instructor-led, live training in Berlin (online or onsite) is aimed at advanced-level professionals who wish to fine-tune and customize AI models on Ollama for enhanced performance and domain-specific applications.
By the end of this training, participants will be able to:
Set up an efficient environment for fine-tuning AI models on Ollama.
Prepare datasets for supervised fine-tuning and reinforcement learning.
Optimize AI models for performance, accuracy, and efficiency.
Deploy customized models in production environments.
Evaluate model improvements and ensure robustness.
This instructor-led, live training in Berlin (online or onsite) is aimed at advanced-level professionals who wish to implement secure and efficient AI-driven workflows using Ollama.
By the end of this training, participants will be able to:
Deploy and configure Ollama for private AI processing.
Integrate AI models into secure enterprise workflows.
Optimize AI performance while maintaining data privacy.
Automate business processes with on-premise AI capabilities.
Ensure compliance with enterprise security and governance policies.
This instructor-led, live training in Berlin (online or onsite) is aimed at intermediate-level professionals who wish to deploy, optimize, and integrate LLMs using Ollama.
By the end of this training, participants will be able to:
Set up and deploy LLMs using Ollama.
Optimize AI models for performance and efficiency.
Leverage GPU acceleration for improved inference speeds.
Integrate Ollama into workflows and applications.
Monitor and maintain AI model performance over time.
This instructor-led, live training in Berlin (online or onsite) is aimed at beginner-level professionals who wish to install, configure, and use Ollama for running AI models on their local machines.
By the end of this training, participants will be able to:
Understand the fundamentals of Ollama and its capabilities.
Set up Ollama for running local AI models.
Deploy and interact with LLMs using Ollama.
Optimize performance and resource usage for AI workloads.
Explore use cases for local AI deployment in various industries.
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