Kurser til virksomheder og offentlige organisationer

This course is designed for engineering leaders who want their teams to build production-ready conversational AI systems. It focuses on the technical and architectural considerations required to design, evaluate, and scale chatbot and dialogue platforms powered by large language models. When completing this course you will be able to:

• Evaluate and integrate LLM-powered chatbots, including retrieval-augmented generation
• Improve reliability and performance through prompt engineering and fine-tuning
• Enhance business impact by incorporating external and web-based data sources

Content & dates: This course is divided into 4 days with 2 modules in each:

• Day 1: LLM & Evaluation Foundations.
• Day 2: Prompt Engineering and Augmenting with Retrieved Information (RAG)
• Day 3: Information Retrieval and Real-time Data for Agents
• Day 4: LLM Fine-Tuning

Prerequisites: To will need the following knowledge to successfully be able to complete the course, either through formal education or self-study. If you are uncertain about complying with the prerequisites, please contact us for an evaluation.

• Knowledge of machine learning - probability theory, linear algebra, classification, neural networks.
• Programming experience in Python

Workload: The total number of hours calculated to be 44 hours distributed as follows:

• Teaching & exercises: 24 hours
• Preparation: 20 hours

Teachers: This course is taught by Associate Professors Daniel Hershcovich & Pepa Kostadinova Atanasova

Price: 30.000 kr.

Note: If there are less than 8 participants, we reserve the right to cancel the course.

This course enables engineering teams to become productive with Python as a core platform for delivering data-driven and machine-learning solutions. By the end of the course, participants can confidently build, maintain, and iterate on end-to-end data and ML pipelines that are ready for real-world use. They also learn how to turn raw data into deployable insights by using Python’s data science and machine-learning ecosystem to ingest, clean, preprocess, and model data.

After participating in this course, your team will be able to:

• Train and optimize models with modern frameworks and automatic differentiation for faster experimentation
• Apply skills directly to real-world datasets, including participants’ own organizational data
• Achieve measurable impact through project-based work supported by curated example datasets

Content & dates: The course is divided into 3 modules consisting of two days:

• Module 1: The Basics of Data Science in Python (20^th & 21^st April 2026)
• Module 2: Introduction to Machine Learning (11^th & 12^th May 2026)
• Project: Solving machine learning problems with own datasets including 1hour project supervision with teacher (between Module 2 & 3)
• Module 3: Deep Learning with Pytorch (1^st & 2^nd June 2026)

Prerequisites: If you are uncertain about complying with the prerequisites, please contact us for an evaluation.

• Basic programming in Python
• Linear algebra (1st year university level)
• Basic concepts of statistics (1st year university level)

Workload: The total number of hours calculated to be 70-80 hours distributed as follows:

• Teaching & exercises: 36 hours
• Preparation: 18 hours
• Project hours: 10-20 hours

Teacher: This course is taught by Associate Professor Oswin Krause

Price: 30.000 kr.

Note: If there are less than 10 participants, we reserve the right to cancel the course.

På Datalogisk Institut kan vi hjælpe dig med at give dine medarbejdere et kompetenceløft som baseres på den nyeste forskning. Vores særligt tilrettelagte virksomhedskurser kan designes til virksomhedens specifikke behov indenfor emner såsom data management, machine learning, AI, softwareudvikling, chatbots & LLMs og meget andet. I kan finde mere inspiration i vores nuværende kursusudbud (scan QR kode). Vi kan afholde kurset hos jer, og vi tager gerne afsæt I jeres cases og data.

Vi har eksperter som kan hjælpe jer, hvis I har brug for at opkvalificere jeres medarbejdere til at opsætte en machine learning model, der kan håndtere jeres databehandling, udvikle/optimere en chatbot specifikt til jeres virksomheds behov, eller hvis jeres softwareudviklere har brug for en opdatering på det nyeste nye inden for computer science.

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