Umap visualisation of profile image thumbnails, Asadchy 2025
Data Visualisation with Python and AI
Introduction to data visualisation, Python basics and the use of AI to create meaningful charts
Dear students, note that this page is updated after the school is over. If you are about to enroll, this page reflect the program from the previous cohort
Overview
The course is designed for people who are interested in improving their ability to analyze and communicate with data. No prior experience in programming or statistics is required, though familiarity with basic data handling will be helpful. The mix of lectures, group discussions, hands-on labs, and project work makes the course accessible to beginners while also offering depth for more advanced students.
Short Programm
Day 1 - Introduction
Introduction to Data VisualisationCreation and study of the visual representation of data., why it is important.
Day 2 – Visual Perception & Cognitive Principles
How humans perceive patterns (Gestalt principles, pre-attentive attributes), colors and what are the most common pitfalls
Day 3 – Data Types & Chart Types
Matching data types to visual forms (categorical, ordinal, quantitative, time series, spatial), the grammar of graphics
Day 4 – Principles of Good Visualization
Edward Tufte’s principles (data-ink ratio, avoiding distortion, maximizing data density), Stephen Few’s guidelines on clarity
Day 5 – Visualizing Time, Space, and Networks
Time series visualization, Geospatial visualization, Network AnalysisMethod to study the relations of actors or other entities in a mediated network. The resulting network is made up of nodes (entities) and edges (relations).
Day 6 – Ethics, Misrepresentation & Persuasion, Storytelling
Cherry-picking, truncating axes, misleading design, exploratory vs. explanatory Data VisualisationCreation and study of the visual representation of data.
Day 7 – AI tools (Google Collab, Anthropic, ChatGPT, Cursor, etc.)
Abilities and limitations of tools
Day 8 – Advanced Prompting, AI Agents
Programming over prompting, skills for AI agents
Day 9 – Workshop: Student Mini-Projects
Framing a visualization project: asking good questions, choosing data, and defining audience
Day 10 – Project Presentations & Course Wrap-Up
Student Presentations, wrap-up notes
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