LexData learning pathways
From your first line of code to advanced AI and Digital Humanities research.
Courses for students, researchers, educators, developers, and professionals who want to connect coding, language, AI, data, and humanistic inquiry.
Choose your level
One learning ecosystem, different starting points.
You do not need to become a software engineer to use computational methods. Start at the level that matches your current work and move forward as your research questions become more ambitious.
Foundation
Students, humanities learners, and first-time coders
Build confidence with Python, data, research computing, AI literacy, and reproducible digital workflows.
Applied
MA / PhD researchers and early-career academics
Use coding, corpus methods, NLP, statistics, and AI to answer real research questions and build publishable projects.
Advanced
Computational researchers and technical specialists
Move into multilingual NLP, computational linguistics, advanced corpus analysis, LLM workflows, and research software.
Professional
Faculty, research labs, institutions, and cross-functional teams
Develop institution-ready AI, data, Digital Humanities, teaching, and research workflows that connect people and technology.
Explore by field
Build a path across code, language, data, and humanities.
The tracks are intentionally connected. A corpus linguist can learn Python, a historian can build an AI-assisted archive workflow, and an NLP researcher can move into application development.
Track 01
Coding foundations
Learn to build, automate, and reason with code.
- Python
- Git and reproducible workflows
- APIs and automation
- Data structures
Find related courses →
Track 02
NLP and computational linguistics
Turn language into analyzable computational data.
- Text preprocessing
- Embeddings and transformers
- Multilingual NLP
- LLMs for language research
Find related courses →
Track 03
AI and Digital Humanities
Bridge humanistic questions with modern AI methods.
- AI-assisted humanities research
- Digital archives
- Cultural and textual data
- Responsible AI
Find related courses →
Track 04
Corpus linguistics
Design, build, annotate, and analyze research corpora.
- Corpus design
- Annotation
- Concordance and collocation
- Corpus statistics
Find related courses →
Track 05
Research and data science
Build evidence-driven research from raw data to publication.
- Research design
- Statistics
- Data visualization
- Reproducible analysis
Find related courses →
Track 06
App development
Turn research ideas into usable digital tools.
- Research applications
- Web and data apps
- AI agents and workflows
- Interactive research tools
Find related courses →
Track 07
Professional skills
Connect technical ability with real academic and professional practice.
- AI literacy
- Research communication
- Data management
- Collaborative project skills
Find related courses →
Cross-level progression
Learn a method. Apply it to research. Build with it.
Understand
Concepts, terminology, computational thinking, and responsible use.
Practice
Hands-on notebooks, corpora, datasets, analysis tasks, and guided projects.
Research
Turn methods into questions, evidence, reproducible analysis, and publication workflows.
Build
Create apps, AI workflows, research tools, datasets, and institution-ready systems.
Published learning
Course catalog
Search by title, topic, category, language, or level.