A one-day intensive course on "Data Analysis Without Code" from the Data Analytics and Social Statistics Master's program
Intensive course teachers
Перехожев Егор Сергеевич
Международная лаборатория прикладного сетевого анализа: Младший научный сотрудник
Irina Pavlova
Международная лаборатория прикладного сетевого анализа: Заместитель заведующего лабораторией
"Data Analysis Without Code" is a one-day intensive course that will immerse participants in modern data analysis methods without programming. Participants will learn how to explore various connections between people, publications, and ideas, as well as how to find patterns in tables and text data.
In the first part of the intensive course, we will explore network analysis: from maps of scientific publications and co-authorship to the analysis of real social connections using the no-code programs VOSviewer and Polinode.
In the second part, participants will try out machine learning and analysis methods, as well as text data visualization in the Orange environment. They will also learn about AI automation and how modern digital assistants work.
This intensive course will therefore cover various data types—networks, tables, and text—that can be analyzed using accessible no-code tools. It includes brief theory and practical examples to demonstrate the full data analysis process, from data collection to interpretation of results.
Intensive program
Topic 1. VOSviewer + Polinode: A Guide to Network Analysis from Bibliometrics to Field Data
| 10:00 – 10:20 | Intensive Course Opening. About the Data Analytics and Applied Statistics Program | Irina Pavlova, ANR-Lab |
| 10:20 – 11:20 | What is bibliometrics and why analyze scientific relationships? Scientific publications as data. What is a citation network, co-authorship, and term co-mention? | |
| 11:20 – 11:30 | Break | |
| 11:30 – 12:50 | Why collect network data? How to ask respondents about their connections? Survey creation in Polinode: questionnaire design, data collection, visualization, and analysis | Anna Kartasheva, ANR-Lab |
| 12:50 – 14:00 | Break | |
Topic 2. Machine learning & AI agents
| 14:00 – 14:40 | What is Data Mining? An overview of the Orange Data Mining interface. Widgets and workflow concepts. | Egor Perekhozhev, ANR-Lab |
| 14:40 – 15:20 | Machine learning without coding. Loading tabular data. Simple visualization (Scatter Plot). Training a classification model (using a decision tree as an example). Assessing model accuracy (Test & Score, Confusion Matrix). | |
| 15:20 – 15:30 | Break | |
| 15:30 – 16:10 | What is AI automation? An introduction to n8n. The n8n interface (workflow, nodes, connections). A breakdown of basic nodes: triggers, logic (conditions, loops), and working with data. | Daniil Kovalev, ANR-Lab |
| 16:10 – 16:50 | Creating an AI agent in n8n. Connecting LLM, tools, and external APIs. Configuring system prompts and organizing dialog context. Integrating with knowledge bases. | |
| 16:50 – 17:00 | Closing remarks and summing up. Presentation of educational opportunities (continuing education programs and master's degree), expertise, and consulting services from the ANR-Lab | Irina Pavlova, ANR-Lab |
Recording of the intensive course
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