garden projects, research & oddities

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University Course Materials

A growing collection of self-study materials shaped by years of teaching data management, analytics, and related subjects at ZČU.

span
2017-now
role
course designer · instructor · primary author
audience
teaching & learning data & research software & tools

topics

tech

Context

During the years I've been teaching at the Faculty of Applied Sciences at the University of West Bohemia, I have worked on and tried to improve course materials for multiple courses that were mostly related to Data management and analytics, Data mining, Database technologies. Usually the primary drive was to update the practicum content to better reflect current technology, workflows, and align it to the lecture curriculum.

While crafting the materials, I tried to focus on how I can make the content more approachable to students and especially to those that need or prefer to take the course at their own pace and/or need to study remotely. I tried to understand and incorporate modern teaching principles to enable an efficient learning experience.

What I Built

The primary artifacts are Czech text-based materials suitable for self-study of practical concepts of various university courses. Relevant topics categorized by courses are:

  • Database Systems 2 — management of XML files via BaseX DB (1, 2), Window functions and CTE in SQL (ref), Geospatial data in PostgreSQL (ref)
  • DB Systems and Data Processing Methods 1 — an entire practicum crafted around data wrangling and shaping into a Data Warehouse-ish structure to allow for answering analytical questions. Showcases real-life issues with data, such as uncertainty in ZIP code mapping to towns, dealing with data snapshots for activity/churn analysis, and handling various input formats. It also highlighted LLM utilization for querying as a modern concept. It was reworked multiple times: the 2026 version (1, 2, 3, 4, 5, 6) is based on Google Colab (Python/Jupyter/Pandas/Matplotlib), previous versions were a local Python project (Python/Pandas/DuckDB) (ref), and a local Java project (ref).
  • DB Systems and Data Processing Methods 2 — an entire practicum crafted around Data Mining, SQL OLAP (ref), Linked Data (ref) and Data Warehousing (via BigQuery). Originally taught using Weka (Java ecosystem) (ref), currently the material is being modernized and transformed into Google Colab (Python/Pandas/Scikit/PyTorch/statsmodels) (1, 2). Historically, the course utilized Power BI for processing and warehousing.
  • Information Systems — initially a specialized practicum showcasing the ETL process via Oracle Data Integrator Studio, which I had to modernize and make approachable for non-technical students from other faculties. I created a series (1, 2, 3, 4, 5) of study texts that tried to show the concepts on a complex real-life problem combining several datasets via Power BI.

Over the years, the materials also evolved in format together with the courses. Older versions were mostly Markdown/HTML study texts, later iterations used local project skeletons, and newer versions moved toward Jupyter/Colab notebooks to make it easier for students to setup.

The materials were reused by other people contributing to the teaching of the courses.

I gave several lectures on specific emerging trends and topics to supplement the lecture tracks that were usually more general and conservatively oriented.

  • Utilization of LLM agents for data querying and exploration (slides).
  • Practical use cases for Linked Data/RDF.

I also participated in teaching other courses while utilizing the existing materials:

Aside from the regular job at the University of West Bohemia, I collaborated with people at Efektivní altruismus Česko to facilitate a course on Biosecurity.

Interesting Problems

  • How to provide the best learning experience — I wasn't formally trained to be in a teaching role, so I had to experiment, adjust, and observe how the students consume the materials and courses, how to motivate them to want to learn, how to structure the final projects and the requirements, etc. This pushed me to educate myself in various psychology and pedagogy subfields and it was also partly my driving force for the job. I wanted to improve the experience for students so there is a chance that later in life they will have the aha moment when they realize the at-the-time obscure concept they learned was actually meaningful in some way.
  • Teaching style and work structure — over time I realized that I want to provide more of a facilitator role and let students discuss alternative options, ask questions, not be afraid to make a mistake and learn from that. This wasn't always possible to deliver though, since some student groups were hard to pull into active engagement with the session/course. Thus I structured the materials in a way that has clear questions and discussion points. I also made most of the final projects individual, so the students are forced to choose a topic/dataset that interests them and work on the project that has meaning to them. Some of the sessions were deliberately made as a consultation on work progress to generate engagement with the students.
  • Attendance at practicums being voluntary — students were not required to be present at sessions, which also affected the decisions about the materials. After experimenting I realized the best way would be to provide detailed walk-through texts, so they can work through that in their free time, but focus more on the discussion and extra bits and thoughts during the in-person session. The sessions were recorded and provided in an unlisted playlist, so students could return to them or watch them if they were unable to come in person. During COVID, we were streaming most of the sessions and were moving towards something that felt more modern and native for me. Unfortunately, this was mostly backpedaled after the pandemic when the faculty returned to in-person sessions, and it left me longing for the times where remote/hybrid was the way to go.