Introduction: Course Overview & Objectives
Learn what you'll accomplish in this 90-minute hands-on course, including prerequisites, deliverables, and success criteria for mastering Claude Projects.
Course Overview
This hands-on course teaches how to leverage Claude Projects for academic research workflows. In 90 minutes, transform how papers are processed by using Claude's 200K context window to analyze 20+ academic papers simultaneously, extract structured information, and synthesize findings into coherent literature reviews with traceable citations.
What This Course Covers: Claude Projects is a workspace feature that maintains persistent context across conversations. This course demonstrates how to set up research-focused projects, upload multiple documents, create reusable instruction sets, and extract insights that would take days of manual work.
Why Claude Projects for Research: Traditional research workflows require reading papers sequentially, manually tracking citations, and synthesizing findings across documents. Claude Projects eliminates these bottlenecks by processing all papers together, maintaining context across analysis sessions, and providing instant cross-document insights with citation tracking.
Who This Course Is For: Researchers, graduate students, and knowledge workers who need to process large volumes of academic literature quickly without sacrificing quality. Anyone who has spent hours manually reading papers and taking notes will benefit from this systematic approach to AI-assisted research.
Prerequisites
Required Before Starting: Completion of T1.1 Prompt Engineering Mastery provides the foundational prompting skills needed for this course. Basic familiarity with academic research processes (reading papers, tracking citations, writing literature reviews) is essential. An active Claude.ai account is required—free tier provides sufficient access for all exercises. Prepare 20 PDF papers in your research area, or use the provided example dataset from AI economics research.
Learning Objectives
By the end of this course, participants will be able to set up and organize Claude Projects with custom instructions and document hierarchies optimized for research workflows. The ability to utilize Claude's 200K token context window for simultaneous multi-document processing will enable analysis of 20+ papers in a single conversation thread. Structured information extraction skills will allow systematic capture of methodology, findings, and contributions from academic papers. Synthesis capabilities will transform extracted information into coherent literature reviews with proper academic framing. Finally, citation tracking and verification techniques will ensure all claims trace back to source documents with accurate attribution.
Deliverables Showcase
Organized Research Project
Fully configured Claude Project containing 20+ processed papers with custom instructions, organized knowledge base, and reusable templates for future research workflows.
Structured Research Synthesis
Coherent literature review exceeding 3,000 words that synthesizes findings across all processed papers with proper academic framing and logical organization.
Citation Database
Comprehensive reference database with 30+ accurately attributed sources, including direct quotes, paraphrased findings, and page number citations ready for academic writing.
Reusable Project Templates
Customizable instruction sets and workflows that can be duplicated for future research projects, saving setup time and ensuring consistent quality across research cycles.
Quality Control Checklist
Systematic verification process for AI-generated research output, including citation accuracy checks, claim verification steps, and output quality benchmarks.
Success Criteria
Successful completion of this course will be demonstrated by the ability to process 20+ academic papers in under 60 minutes from initial upload to final synthesis, a dramatic improvement over traditional manual research methods. The generated literature review must be coherent, well-structured, and include proper citations that match academic standards for literature reviews. Every claim in the synthesis must be verifiable—participants should be able to trace each assertion back to specific source documents with page numbers or section references. Finally, the output quality should match or exceed what would be produced through manual research, as evaluated by subject matter experts or through self-assessment against previous research work.
Time Investment Breakdown
This 90-minute course is structured with a 10-minute introduction to course objectives and prerequisites, followed by a 15-minute quick start session that delivers first wins by setting up a basic Claude Project and processing initial papers. The core build phase requires 45 minutes to upload all papers, create comprehensive custom instructions, and generate the full literature review synthesis. Three 5-minute domain application sessions demonstrate how to adapt workflows for economics research, software engineering documentation, and business strategy analysis. The final segments include 5 minutes for troubleshooting common issues and 5 minutes for exploring extension patterns and next steps in AI-assisted research.
This structured approach ensures participants achieve hands-on mastery of Claude Projects for research while building deliverables that provide immediate value to their ongoing work.
Claude Projects for Research: Process 20 Papers in 60 Minutes
Master Claude Projects to transform how you conduct literature reviews. Learn to process 20+ academic papers, generate comprehensive syntheses, and track citations in under an hour.
Quick Start: Your First Research Project in 15 Minutes
Get hands-on immediately. Create your first Claude Project, upload 3 sample papers, configure custom instructions, and generate your first research synthesis.