Course
AI for Research
For PhD students, journalists, consultants, analysts. Search and discovery, academic tools, source analysis, writing and synthesis, and verification.
- Length
- ~8 hours + research project
- Structure
- 8 modules · 29 lessons
- Certificate
- Verifiable on completion
Coming soon
This course is still in development. The structure below is a preview of what will be available — modules and lesson titles may change as we build it.
1
Research with AI: Foundations
- Where AI helps and where it hurts in research
- Citation hygiene and AI
- Bias and selection effects in AI research
2
Search & Discovery
- Perplexity Pro and Deep Research
- Claude with web search
- Gemini Deep Research
- When to use which
3
Academic Research Tools
- Elicit
- Consensus
- SciSpace
- Semantic Scholar with AI
- Building literature review pipelines
4
Document & Source Analysis
- NotebookLM for source synthesis
- Long-document analysis with Claude/Gemini
- Comparing across multiple sources
- Extracting structured data from PDFs
5
Writing & Synthesis
- From sources to argument
- AI as a thinking partner (not a writer)
- Outline-driven writing workflows
- Avoiding AI sludge in your writing
6
Verification & Fact-Checking
- The verification habit
- Source-checking workflows
- Detecting AI hallucinations in research
- When to walk back AI-assisted claims
7
Disclosure in Research Contexts
- Academic norms
- Journalism standards
- Consulting and analyst contexts
- Building your personal research disclosure standard
8
Capstone
A complete research artifact — literature review, investigative piece, or analyst report — with documented AI workflow and disclosure.
- Capstone Project