The wide range of educational training programs offered by the AI Service Center allows you to get started in the field of AI and deepen your knowledge in the areas of artificial intelligence that interest you most.
Different learning levels enable you to find just the right level of complexity and detail you need. Varying formats, such as online courses, workshops, and classroom lectures, allow you to choose the learning method that suits you best.
Below you find a current list of educational training offerings, including information on how to register.
This learning level is designed for anyone who has heard about artificial intelligence in the media but has not yet been able to grasp what this hype is all about and what artificial intelligence can and cannot do. In these entertaining, professional programs, we introduce you to AI and give you insights into its many opportunities and challenges.
Do you have an AI idea, a technical challenge, or simply a question about how artificial intelligence could support your project? The AI Café is the place to bring it! Exchange ideas directly with experts from the hessian.AI Service Center, get practical guidance for your individual use case, and discover new approaches to move your AI project forward. Whether you are taking your first steps with AI or already working on a concrete application, the AI Café gives you the opportunity to ask questions, discuss solutions, and benefit from expert knowledge in an open setting. Join us twice a month, online and in German or English.
The AI Academy offers a low-threshold introduction for those interested in AI who want to gain an overview of the many opportunities artificial intelligence offers while also acquiring entrepreneurial skills. Fundamental knowledge of AI applications, combined with practical relevance for various industries as well as society, provide a solid foundation for deeper immersion in more specific areas of artificial intelligence.
At this learning level, our programs dig deeper into how artificial intelligence can be developed, customized, applied, and played with. To ensure that these modules are both fun and valuable, participants should bring a basic understanding of AI, Python programming, and data management.
HeFDI – Hessian Research Data Infrastructures provides comprehensive information on a variety of topics, ranging from HeFDI Code School, which offers comprehensive knowledge for efficient and clean programming, and the HeFDI Data Talks, which transfer in-depth knowledge of data management, to the HeFDI Data School.
→ More information about the Hessian Research Data Infrastructures can be found at HeFDI
At this learning level, you gain insights into current AI research and its challenges, as well as into the solutions and approaches our researchers have developed to date. In entertaining lectures and presentations, you not only get new impulses for your everyday life, but also an honest and unfiltered view into the current state of research.
Enterprises need to execute language-related tasks daily, such as text classification, content generation, sentiment analysis, and customer chat support, and they seek to do so in the most cost-effective way. Large language models can automate these tasks, and efficient LLM customization techniques can increase a model’s capabilities and reduce the size of models required for use in enterprise applications.
In this course, you’ll go beyond prompt engineering LLMs and learn a variety of techniques to efficiently customize pretrained LLMs for your specific use cases—without engaging in the computationally intensive and expensive process of pretraining your own model or fine-tuning a model’s internal weights. Using NVIDIA NeMo™ service, you’ll learn various parameter-efficient fine-tuning methods to customize LLM behavior for your organization.
Learn how to apply and fine-tune a Transformer-based Deep Learning model to Natural Language Processing (NLP) tasks. In this course, you’ll:
Upon completion, you’ll be proficient in task-agnostic applications of Transformer-based models.
Recent advancements in both the techniques and accessibility of large language models (LLMs) have opened up unprecedented opportunities to help businesses streamline their operations, decrease expenses, and increase productivity at scale. Additionally, enterprises can use LLM-powered apps to provide innovative and improved services to clients or strengthen customer relationships. For example, enterprises could provide customer support via AI companions or use sentiment analysis apps to extract valuable customer insights.
In this course you will gain a strong understanding and practical knowledge of LLM application development by exploring the open-sourced ecosystem including pretrained LLMs, enabling you to get started quickly in developing LLM-based applications.
Businesses worldwide are using artificial intelligence to solve their greatest challenges. Healthcare professionals use AI to enable more accurate, faster diagnoses in patients. Retail businesses use it to offer personalized customer shopping experiences. Automakers use AI to make personal vehicles, shared mobility, and delivery services safer and more efficient. Deep learning is a powerful AI approach that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation. Using deep learning, computers can learn and recognize patterns from data that are considered too complex or subtle for expert-written software
Thanks to improvements in computing power and scientific theory, generative AI is more accessible than ever before. Generative AI plays a significant role across industries due to its numerous applications, such as creative content generation, data augmentation, simulation and planning, anomaly detection, drug discovery, personalized recommendations, and more. In this course, learnes will take a deeper dive into denoising diffusion models, which are a popular choice for text-to-image pipelines
