Want to make your data analysis more efficient without compromising research rigor? Join Dr Kimberly Fessel for a one-day, hands-on online seminar on using ChatGPT alongside Jupyter and Python in research workflows. Designed for PhD students, postdocs, faculty, and research professionals with basic familiarity with Python and statistics, the workshop covers data cleaning, exploratory analysis, coding and debugging, visualization, and synthetic data generation. You’ll also practice validating AI-generated outputs, keeping your work reproducible, and protecting sensitive data—using AI as an assistant, not a substitute for your expertise. Attend live via Zoom or revisit the recording and materials for 30 days afterward, with access to an expert-monitored Q&A forum. #ArtificialIntelligence #ComputationalSocialScience #DataAnalytics #DataScience #Statistics #ComputerScience #InformationScience #SoftwareEngineering #ChatGPT #Jupyter #Python #Research #ResearchTraining #Instats

VideoParl is a DFG-funded research project analyzing text, audio and video from German parliamentary debates.

Political and social scientists are working with more text than ever, from parliamentary speeches and treaty preambles to government reports, news coverage, social media posts, and policy documents. This 3-day intensive online seminar shows PhD students and professional researchers how to use large language models to turn complex text into defensible, analysis-ready data without requiring prior machine learning or Python experience. Through live Google Colab demonstrations, participants will learn when to use encoder models such as BERT and DeBERTa, when generative models such as GPT or Claude are more appropriate, how to apply zero-shot classification, build and validate gold-standard datasets, evaluate performance with metrics such as accuracy, F1 scores, Cohen’s kappa, and confusion matrices, and create end-to-end pipelines for extracting and cleaning data from PDFs, websites, and other messy sources. The seminar is designed to help researchers strengthen methodological credibility, accelerate data collection and coding, and expand the range of research questions that can be tackled with text. All sessions are livestreamed via Zoom, with recordings, slides, code, data, and a monitored Q&A forum available for 30 days after the seminar, plus an official Instats certificate of completion. #ArtificialIntelligence #ComputationalSocialScience #PoliticalScience #ComputerScience #Statistics #DataScience #InformationScience #SocialTheory #Sociology #Claude #GoogleColab #HuggingFace #Jupyter #Python #Research #ResearchTraining #Instats

Social networks are essential for studying diffusion, influence, segregation, cooperation, inequality, and many other relational processes — but analyzing network data well requires methods that account for dependence, structure, measurement, and privacy. Join our one-day online workshop, Modern Statistical Methods for Networks, led by Professor Tianxi Li from the School of Statistics at the University of Minnesota, Twin Cities, for a focused, hands-on introduction to research-grade network analysis in R. Designed for PhD students, faculty, and professional researchers, the workshop will cover network representations and descriptive summaries, statistical inference, stochastic block and latent-space models, community detection, link prediction, attributed network analysis, privacy-preserving data release, and reproducible R workflows for simulation, estimation, diagnostics, and visualization. Participants will gain practical skills for selecting and fitting appropriate models, evaluating assumptions, building defensible link-prediction pipelines, incorporating covariates, and translating empirical questions into reproducible analytic plans suitable for publications and grant work. The seminar is livestreamed via Zoom, with recordings, materials, datasets, code, and a monitored Q&A forum available for 30 days after the session, and participants receive an official Instats certificate of completion. #ComputationalSocialScience #DataScience #SocialTheory #Statistics #MachineLearning #PublicPolicy #Sociology #ComputerScience #R #Research #ResearchTraining #Instats

How can researchers use large language models without compromising causal rigor? Join our online seminar on Causal Inference and Large Language Models, designed for PhD students, postdoctoral researchers, and academic staff working with textual, social media, administrative, or mixed-format data. Taught by Moses Boudourides (Northwestern University), this seminar explores how LLMs can be integrated into causal inference workflows to measure latent constructs, generate candidate instruments, support causal discovery, estimate treatment effects with high-dimensional text data, and audit bias in LLM-derived variables. Participants will engage with conceptual foundations and applied workflows using reproducible, fully annotated Python and R scripts, diagnostic tools, and publication-oriented strategies. No prior knowledge of causal inference, LLMs, programming, or coding is required; general familiarity with quantitative research is sufficient. The seminar is delivered online via Zoom, with recordings, slides, scripts, data, readings, and a monitored Q&A forum available for 30 days after the seminar. Participants receive an official Instats certificate of completion, with ECTS Equivalent points where applicable. #AppliedResearch #BayesianStatistics #CausalInference #ComputationalSocialScience #ComputationalStatistics #ComputerScience #DataScience #Economics #EnvironmentalSciences #Finance #Healthcare #MachineLearning #Management #MixedMethods #OrganizationStudies #RegressionModelingStrategies #ResearchMethods #SocialSciences #Sociology #Statisticalmodellingandregression #Statistics #SocialTheory #Python #R #Research #ResearchTraining #Instats

Researchers increasingly rely on online information as empirical evidence, but turning heterogeneous web sources into reliable, analysis-ready data requires the right methodological and technical foundations. This online Instats seminar, led by Moses Boudourides of the Data Science Graduate Program at Northwestern University, offers PhD students, postdoctoral researchers, and professional researchers a rigorous, hands-on introduction to web scraping and structured data collection for academic research. Participants will learn how to identify suitable web data sources, use no-code and programmatic approaches in Python and R, parse HTML and JSON, work with APIs and dynamic content, clean and validate messy outputs, document provenance, and integrate collection workflows into reproducible research pipelines. The seminar also addresses responsible and ethical data collection, including rate limiting, terms of service, and best practices for working with human-generated content. Designed to support publishable empirical work across fields such as computational social science, finance, health sciences, and the life sciences, the seminar provides reusable scripts, templates, cleaned sample files, and documentation tools that participants can adapt directly to their own research projects. Livestream sessions are delivered via Zoom, with recordings, materials, and a monitored Q&A forum available for 30 days afterward; participants also receive an official Instats certificate of completion. #AppliedResearch #ComputationalSocialScience #DataScience #DataScraping #Finance #HealthSciences #LifeSciences #Statistics #ComputerScience #InformationScience #SoftwareEngineering #Python #R #Research #ResearchTraining #Instats

Join us for a three-day online workshop on using Large Language Models (LLMs) for qualitative social network research, taught by Professor Moses Boudourides of Northwestern University. Designed for PhD students, academic researchers, and professional researchers across anthropology, sociology, communication, media studies, organization studies, public policy, social psychology, and related fields, this hands-on seminar explores how LLMs can support qualitative coding, entity and relation extraction, socio-semantic network construction, validation, visualization, and reproducible research workflows. Participants will work in Python/Jupyter with practical notebooks and real research problems, learning how to extract actor relationships from interviews and social media, build actor–topic and actor–attribute networks, integrate outputs with NetworkX/igraph/graph-tool, assess uncertainty and bias, and document methods for peer-reviewed publications, dissertations, and grant proposals. The workshop combines methodological rigor, ethical reflection, and immediately applicable code, with live Zoom sessions, access to recordings and materials for 30 days, a monitored Q&A forum, and an official Instats certificate of completion. #Anthropology #Communication #ComputationalSocialScience #ComputerScience #Ethnography #Management #Media #OrganizationStudies #SocialMedia #SocialNetworkAnalysis #SocialPolicy #SocialPsychology #Sociology #PublicPolicy #SocialTheory #Statistics #DataScience #InformationScience #Ethics #Jupyter #Python #Research #ResearchTraining #Instats

Join us for a three-day online workshop with Professor Moses Boudourides (Data Science Graduate Program, Northwestern University) exploring how Large Language Models (LLMs) and Knowledge Graphs (KGs) can transform scholarly synthesis, systematic reviews, and theoretical discovery. Designed for PhD students, faculty, and professional researchers, this hands-on seminar series combines conceptual foundations with practical Python-based workflows delivered through reproducible Jupyter Notebooks. Across three sessions, participants will learn how to build LLM-augmented knowledge graphs, automate literature discovery, screening, and extraction, visualize theoretical landscapes, evaluate extraction quality, manage uncertainty, and design human-in-the-loop workflows that reduce hallucination risk while preserving scalability. Topics include prompt engineering, entity and relation extraction, semantic search, bibliometric and network analysis, theory mapping, provenance tracking, and responsible AI use in academic research. All sessions are livestreamed via Zoom, with recordings, slides, code, data, and a monitored Q&A forum available for 30 days after the seminar, making it easy to participate live or asynchronously. Participants receive an official Instats certificate of completion, with ECTS Equivalent points available where applicable. disciplines #ArtificialIntelligence #BibliometricResearch #ComputationalSocialScience #ComputerScience #DataScience #InformationScience #MachineLearning #Management #Multidisciplinary #SocialTheory #Linguistics #Ethics #PhilosophyofScience #CognitiveScience #Statistics #Python #Research #ResearchTraining #Instats

Unlock new ways to model complexity with our online seminar on Hypernetworks and Hypergraphs, designed for PhD students, academics, and professional researchers working with interconnected systems. Led by Professor Moses Boudourides from the Data Science Graduate Program at Northwestern University, this four-day workshop combines theoretical foundations with hands-on Python applications to help participants analyze higher-order and multidimensional relationships that traditional network models cannot fully capture. Topics include hypergraph definitions and visualization, structural metrics, centrality, community partitioning, simplicial complexes, temporal hypergraphs, contagion models, random hypergraphs, clustering, and hyperlink prediction. With applications across computational biology, bibliometrics, chemical reaction networks, social and health network analysis, and more, the seminar equips researchers with practical tools for generating new insights into complex systems. Participants receive access to recordings and materials for 30 days, take-home skill challenges, instructor-supported discussion, and an official Instats certificate of completion, with ECTS Equivalent points available for European students. #ComputerScience #DataScience #InformationScience #ComputationalBiology #ComputationalSocialScience #SocialNetworkAnalysis #DigitalHumanities #Multidisciplinary #CognitiveScience #Biology #Statistics #Mathematics #Biostatistics #Python #Research #ResearchTraining #Instats

Join our comprehensive 5-day online workshop on Network Analysis with Python, designed for PhD students, academics, and professional researchers who want to apply network science to complex data across the natural and social sciences. Led by Professor Moses Boudourides, this hands-on seminar will guide participants through constructing and analyzing networks using Python and NetworkX, including graph types, adjacency matrices, connectivity, motifs, centrality, communities, subgraphs, paths, and network structure. Through practical coding sessions, real-world examples, discussions, and take-home skill challenges, participants will gain the tools to uncover hidden patterns, identify influential nodes, evaluate network dynamics, and apply computational network science methods to their own research. The seminar is delivered live via Zoom, with recordings, slides, code, data, and materials available for 30 days after the workshop, along with access to an instructor-monitored discussion forum. An official Instats certificate of completion is provided, with ECTS Equivalent points available for European students. #Engineering #ComputerScience #DataScience #InformationScience #Mathematics #Communication #OrganizationStudies #SocialSciences #InformationSystems #ComputationalSocialScience #SocialNetworkAnalysis #DigitalHumanities #Python #Research #ResearchTraining #Instats

Ready to move from “I’d like to use text-as-data” to actually building and running your own pipeline? This three-day hands-on online seminar is designed for PhD students and professional researchers in the social sciences who want to apply text-as-data methods without getting stuck on the programming. Starting from no coding background, you’ll learn the Python you actually need, link messy datasets using spelling and semantic similarity, model themes with LDA and the Structural Topic Model, and work with BERT-based encoder models to classify political text at scale. By the end, you’ll have fine-tuned, validated, saved, and reused your own language model in free browser-based notebooks, with every step scaffolded and supported. The seminar is delivered live via Zoom in three 2.5-hour sessions, with recordings, materials, and a monitored Q&A forum available for 30 days afterward, plus an official Instats certificate of completion. #ComputationalSocialScience #PoliticalScience #ComputerScience #DataScience #Statistics #GoogleColab #Jupyter #Python #Research #ResearchTraining #Instats

Join us for a three-day online workshop, “Large Language Models and Knowledge Graphs for Scholarly Synthesis and Theoretical Discovery,” taught by Professor Moses Boudourides of the Data Science Graduate Program at Northwestern University. Designed for PhD students, faculty, and professional researchers, this hands-on seminar explores how LLMs can be integrated with Knowledge Graphs to support automated literature discovery, systematic reviews, evidence synthesis, and theory mapping across research domains. Participants will work with Python-based Jupyter Notebooks and practical workflows for KG construction, entity and relation extraction, semantic search, bibliometric and network analysis, visualization, provenance tracking, uncertainty assessment, and human-in-the-loop validation. Across three focused sessions, the workshop covers LLM-augmented Knowledge Graph construction, automated systematic review pipelines, and theory mapping for identifying conceptual relationships, clusters, and research gaps. All livestreaming sessions are delivered via Zoom, with recordings, slides, code, data, and an online Q&A forum available for 30 days after the seminar, making it easy to participate live or asynchronously. Participants receive an official Instats certificate of completion, with ECTS Equivalent points available where applicable. disciplines #ArtificialIntelligence #BibliometricResearch #ComputationalSocialScience #ComputerScience #DataScience #InformationScience #MachineLearning #Management #Multidisciplinary #SocialTheory #Linguistics #Ethics #PhilosophyofScience #CognitiveScience #Statistics #Python #Research #ResearchTraining #Instats

Abstract Generative artificial intelligence (GenAI) has field-level implications for computational communication research (CCR), not only by expanding methodological repertoires, but also by reshaping...

Ready to bring text-as-data methods into your research without getting stuck on the programming? This three-day, hands-on online seminar is designed for PhD students and professional researchers in the social sciences who have little or no coding background and want to learn practical Python for working with text. Across live Zoom sessions using free browser-based notebooks, you will move from your first lines of Python to building a complete text-as-data pipeline: linking messy datasets by spelling and semantic meaning, modeling themes with LDA and the Structural Topic Model, understanding BERT-based encoder models, and fine-tuning your own classifier to place political text on a left-right scale. The seminar builds on familiar R and Stata intuitions, requires no prior Python or machine learning experience, and includes step-by-step support throughout. Recordings, slides, code, data, and outputs are available for 30 days after the seminar, with a monitored Q&A forum for follow-up questions, and participants receive an official Instats certificate of completion. #ComputationalSocialScience #PoliticalScience #ComputerScience #DataScience #Statistics #GoogleColab #Jupyter #Python #Research #ResearchTraining #Instats

Unlock the potential of web-derived data for rigorous, publishable research in this online seminar designed for PhD students, postdoctoral researchers, and professional academics. Led by Moses Boudourides of the Data Science Graduate Program at Northwestern University’s School of Professional Studies, this research-focused seminar introduces practical and reproducible approaches to web scraping and structured data collection across fields such as computational social science, finance, health sciences, and the life sciences. Participants will learn how to identify suitable online data sources, use no-code and programmatic extraction methods in Python and R, parse HTML, JSON, APIs, and dynamic web content, clean and validate messy outputs, document provenance, and build reproducible workflows that meet the expectations of reviewers and journals. The seminar also addresses ethical and legal considerations, rate limiting, polite scraping practices, and responsible reuse of online data. With hands-on examples, reusable templates, cleaned sample files, documentation tools, and access to recordings, materials, and a monitored Q&A forum for 30 days, participants will leave with concrete skills and artifacts they can immediately apply to their own empirical research projects. An official Instats certificate of completion is provided. #AppliedResearch #ComputationalSocialScience #DataScience #DataScraping #Finance #HealthSciences #LifeSciences #Statistics #ComputerScience #InformationScience #Python #R #Research #ResearchTraining #Instats

AI is transforming the way researchers work with data, and this one-day hands-on online workshop is designed to help PhD students, postdocs, faculty, and research professionals use these tools effectively, responsibly, and reproducibly. Led by Dr Kimberly Fessel, the seminar focuses on practical AI-assisted data analysis using ChatGPT alongside Jupyter and Python workflows, with applications in data cleaning, exploratory analysis, coding, debugging, visualization, synthetic data generation, and validation of AI-generated outputs. Participants will learn how to use AI as a research assistant while maintaining statistical rigor, domain expertise, and human judgment, with supervised exercises and immediately applicable techniques for real research workflows. The seminar is delivered live via Zoom, with recordings, materials, and a Q&A forum available for 30 days afterward, and participants receive an official Instats certificate of completion. #ArtificialIntelligence #ComputationalSocialScience #DataAnalytics #DataScience #Statistics #ComputerScience #InformationScience #SoftwareEngineering #ChatGPT #Jupyter #Python #Research #ResearchTraining #Instats

Join our online seminar on Web Scraping in Python for scholarly research, designed for PhD students and professional researchers who want to turn web-based information into structured, analysis-ready data. Led by Kimberly Fessel of Dr Kim Data, this practical workshop covers HTML, the DOM, browser developer tools, requests, BeautifulSoup, reproducible scraping pipelines, data cleaning, JavaScript-rendered pages, Playwright, rate limiting, robots.txt, and responsible data collection practices. Participants will learn how to extract text, links, tables, and other research-relevant content across multiple web pages, while also developing the methodological judgement needed to decide when scraping, APIs, or downloadable datasets are the best choice. Suitable for researchers across the social sciences, public health, environmental studies, digital humanities, media, and computational fields, the seminar includes Zoom livestream access, 30-day access to recordings and materials, a monitored Q&A forum, and an official Instats certificate of completion. #AppliedResearch #Biology #Business #ComputationalSocialScience #DataAnalytics #DataScience #DataScraping #DigitalHumanities #EnvironmentalSciences #Media #PoliticalScience #PublicHealth #Real-WorldData #SocialMedia #SocialSciences #Statistics #InformationScience #ComputerScience #Python #Research #ResearchTraining #Instats

In this article, we advocate for qualitative research using LLM chatbots. While qualitative research may seem incompatible with generative artificial intelligen...

Generative AI is changing the way researchers work with data — and knowing how to use it responsibly can make research workflows faster, clearer, and more reproducible. Join Dr Kimberly Fessel for a one-day, hands-on online workshop on practical, research-focused applications of generative AI using ChatGPT, Jupyter, and Python. Designed for PhD students, postdocs, faculty, and research professionals, the workshop will cover AI-assisted data cleaning, exploratory data analysis, visualization, code explanation and function creation, prompt engineering, and synthetic data generation, with an emphasis on preserving scientific rigor and auditability. Participants will work through applied exercises using reproducible notebooks, ready-to-use templates, and research-relevant examples, leaving with concrete skills they can immediately apply to their own data workflows. The seminar is offered live via Zoom, with recordings, materials, and a monitored Q&A forum available for 30 days afterward, plus an official Instats certificate of completion. #ArtificialIntelligence #ComputationalSocialScience #DataAnalytics #DataScience #Statistics #ComputerScience #InformationScience #SoftwareEngineering #ChatGPT #Jupyter #Python #Research #ResearchTraining #Instats

How can Large Language Models be used to design better experimental treatments while maintaining rigor, validity, ethics, and reproducibility? Join our four-day online workshop with Professor Charles Crabtree (Dartmouth College) to learn practical, research-ready workflows for using ChatGPT and R in experimental treatment design. Designed for PhD students, faculty, and applied researchers in the social sciences and policy, this hands-on seminar covers prompt engineering, multi-version vignette generation, chat-based interventions, lexical balance and readability checks, validation routines, preregistration, IRB considerations, and transparent reporting practices. Across four live 1.5-hour Zoom sessions, participants will work with prompt templates, R scripts, reproducible notebooks, and adaptable exercises that can be applied directly to their own projects. No advanced coding background is required. Recordings and materials will be available for 30 days after the seminar, and participants will receive an official Instats certificate of completion. #ComputationalSocialScience #PoliticalEconomy #PoliticalScience #PublicPolicy #SocialPolicy #Sociology #ComputerScience #Statistics #SocialTheory #InformationScience #Ethics #DataScience #ChatGPT #R #Research #ResearchTraining #Instats