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
- 1Where AI helps and where it hurts in research
- 2Citation hygiene and AI
- 3Bias and selection effects in AI research
2
Search & Discovery
- 1Perplexity Pro and Deep Research
- 2Claude with web search
- 3Gemini Deep Research
- 4When to use which
3
Academic Research Tools
- 1Elicit
- 2Consensus
- 3SciSpace
- 4Semantic Scholar with AI
- 5Building literature review pipelines
4
Document & Source Analysis
- 1NotebookLM for source synthesis
- 2Long-document analysis with Claude/Gemini
- 3Comparing across multiple sources
- 4Extracting structured data from PDFs
5
Writing & Synthesis
- 1From sources to argument
- 2AI as a thinking partner (not a writer)
- 3Outline-driven writing workflows
- 4Avoiding AI sludge in your writing
6
Verification & Fact-Checking
- 1The verification habit
- 2Source-checking workflows
- 3Detecting AI hallucinations in research
- 4When to walk back AI-assisted claims
7
Disclosure in Research Contexts
- 1Academic norms
- 2Journalism standards
- 3Consulting and analyst contexts
- 4Building your personal research disclosure standard
8
Capstone
A complete research artifact — literature review, investigative piece, or analyst report — with documented AI workflow and disclosure.
- 1Capstone Project