Building Generative AI Based Applications With LLMs and Data Augmentation Architectures

Conference Center ADN, room 12

Join us for a one-day workshop on Generative AI and large language models. This event aims to provide participants in-depth knowledge of the latest advancements in natural language processing, computer vision, and machine learning techniques for Gen AI.

The workshop will explore real-life applications of large language models using cutting-edge models such as GPT, PalM, Gemini, and open-source LLMs. Participants will also learn how to use industry-standard LLMs with APIs, fine-tune models on their data, and deploy private LLM-based assistants.

Upon completing the workshop, attendees will gain a comprehensive understanding of integrating Generative AI into data solutions.

   Target Audience

Data Scientists, Machine Learning Engineers and Software Engineers who are interested in building solutions based on Generative AI.


  • Some experience coding in Python, basic understanding of cloud computing and machine learning concepts
  • Laptop with IDE and web browser
  • No prior experience with Generative AI needed

    Participant’s ROI

  • Practical knowledge of building Generative AI solutions using open-source tools
  • Hands-on experience with building Generative AI powered applications
  • Tips about real world applications and best practices

    Training Materials

All participants will get training materials in the form of PDF files containing slides with theory and exercise manual with the detailed description of all exercises.

    Time Box

This is a one-day event (9.00 - 16.00), there will be some breaks between sessions.


  • Session #1 - Generative AI and Large Language Models (LLM)
    • Short recap: basic concepts and terminology
    • Technology landscape
    • How can you use it on your projects? Let’s discuss the Generative AI use cases
    • Compliance and information security considerations
  • Session #2 - Generative AI on Google Cloud Platform and prompt engineering
    • The capabilities of Google Cloud Platform for Generative AI (Model Garden, Generative AI Studio)
    • Prompt engineering (hand-on labs)
  • Session #3 and #4 - Retrieval Augmented Generation (RAG) architecture in practice with open-source tools (hands-on labs)
    • Interfaces for LLM models: LangChain, LLamaIndex
    • Building the conversational interface to the documents database with Vertex AI PaLM API


large language models, generative ai, retrieval augmented generation

    Session leader:

Machine Learning Engineer
GetInData | Part of Xebia
Chief Data Architect
GetInData | Part of Xebia



Evention sp. z o.o

Rondo ONZ 1 Str,

Warsaw, Poland


Weronika Warpas