Learn to query blockchain data, integrate market and protocol data, analyze datasets in Excel, build custom dashboards and use AI to improve analytical workflows. Applied research verticals include DeFi, real-world asset tokenization and perpetual futures.
SQL queries and documented onchain findings
Excel workbook integrating market and onchain data
Comparative DeFi dashboard and research brief
RWA market intelligence workbook and memo
Perpetual futures dashboard and market report
Final portfolio project and presentation
Six-week curriculum
Each week includes two instructor-led sessions, a Friday office hour and a practical project. Follow the sequence from foundations to capstone without tying the curriculum to calendar dates.
Week 1
SQL for Onchain Data & Research Foundations
Translate blockchain research questions into measurable metrics, then query real onchain datasets.
Tools and methods: Dune · SQL · AI assistants
Live sessions
Session 1: Research Questions and Blockchain Data
Onchain research workflows; blocks, transactions, wallets, smart contracts and events
Introduction to Dune and blockchain data schemas
Turning a research question into measurable metrics
AI lab: formulate research questions and explain blockchain concepts
Session 2: SQL for Analytical Queries
Filtering, aggregation, joins, CTEs and window functions
Date-based analysis and daily activity metrics
Calculate transactions, active wallets, fees and growth rates
AI lab: generate, explain, debug and validate SQL queries
Friday office hours: Friday, 13 November — SQL troubleshooting, query reviews, research question refinement and project clinic.
Weekly project: Analyze a selected blockchain’s activity and produce a documented SQL analysis with an initial set of findings.
Week 2
Excel, APIs & Multi-Platform Data Integration
Clean, combine and analyze market and onchain datasets in a reusable Excel workbook.
Tools and methods: Excel · Power Query · CoinGecko API · Dune
Live sessions
Session 3: Excel for Data Analysts
Import CSV files and structured datasets
Clean, format, deduplicate and validate data
XLOOKUP, SUMIFS, COUNTIFS, IFERROR and date functions
Percentage change, growth rates and basic financial calculations; AI formula lab
Session 4: Connecting Data Sources and Building Dashboards
CoinGecko market data and API fundamentals
Refresh data with Power Query where supported
Combine token prices with Dune onchain metrics
Pivot tables, charts, slicers and conditional formatting; AI-assisted transformations and dashboard layouts
Friday office hours: Friday, 20 November — Excel formula clinic, API and data-import troubleshooting, workbook and data-quality review.
Weekly project: Build an interactive Excel workbook combining CoinGecko market data with a selected onchain dataset, including cleaned data, calculated metrics, pivot tables and charts.
Week 3
DeFi Protocol Intelligence
Compare protocols using TVL, trading volume, fees, revenue, liquidity and onchain activity.
Tools and methods: SQL · DefiLlama · Excel · Dune
Live sessions
Session 5: DeFi Metrics and Protocol Analysis
Understand TVL, trading volume, fees, revenue and liquidity
Introduction to DefiLlama and relevant protocol data sources
SQL-based protocol activity analysis
Compare protocols in the same category; AI-assisted metric selection and SQL explanations
Session 6: DeFi Research Dashboards
Combine protocol metrics with onchain and market data
Growth analysis, market share and concentration
Excel dashboards for protocol comparisons
Interpret findings and limitations; AI-assisted chart selection and research outlines
Friday office hours: Friday, 27 November — DeFi project reviews, dashboard feedback, research methodology and metric validation.
Weekly project: Compare three DeFi protocols in the same category. Submit an Excel dashboard and short research brief on growth trends, performance differences and potential risks.
Week 4
RWA & Tokenization Research
Investigate tokenized real-world assets with careful definitions, source checks and comparable metrics.
Tools and methods: RWA data sources · Excel · SQL · AI research tools
Live sessions
Session 7: Understanding Tokenized Assets
Tokenized Treasuries, funds and other real-world assets
Identify issuers, asset categories and blockchain networks
Explore RWA data sources and their definitions
Analyze supply, market share and historical changes where data is available; AI evidence-mapping lab
Session 8: RWA Data Modelling and Research
Import and clean RWA datasets
Calculate growth, concentration and issuer comparisons in Excel
Design an RWA market intelligence dashboard
Distinguish tokenized supply, market capitalization, trading volume and underlying asset value; AI consistency checks
Friday office hours: Friday, 4 December — RWA dataset and source reviews, Excel modelling support and feedback on preliminary findings.
Weekly project: Produce an RWA market intelligence workbook and research memo examining a selected tokenized asset category, its major issuers and market trends.
Week 5
Perpetual Futures & Market Structure
Use derivatives metrics to understand market activity, positioning and changing conditions.
Tools and methods: SQL · Excel · Perpetual futures datasets
Live sessions
Session 9: Derivatives Data and Market Metrics
Introduction to perpetual futures and funding rates
Open interest, trading volume and liquidations
Identify historical data sources and available datasets
Analyze market activity and changes over time with SQL; AI query-validation lab
Session 10: Market Research Dashboards
Excel-based funding rate and open-interest analysis
Rolling averages, percentage changes and market comparisons
Compare price movements with derivatives metrics
Build a perpetual futures dashboard; use AI to challenge assumptions and structure a report
Friday office hours: Friday, 11 December — derivatives data troubleshooting, dashboard and calculation reviews, capstone topic selection.
Weekly project: Analyze a selected perpetual futures venue or group of markets. Produce a dashboard and short report describing market structure, observed trends and analytical limitations.
Week 6
AI-Assisted Research, Capstone & Publication
Bring SQL, Excel and research narrative together in a reproducible, portfolio-ready deliverable.
Tools and methods: SQL · Excel · AI assistants · Research documentation
Live sessions
Session 11: Research Workflows and AI
Formulate a research question and measurable hypotheses
Combine SQL results, Excel analysis and external data sources
Use AI to review query logic, formulas and research structure
Verify evidence, document sources and support reproducibility
Write executive summaries; protect credentials and verify AI-generated outputs
Session 12: Capstone Presentations
Demonstrate final dashboard and workbook
Present research methodology and findings
Peer review and instructor feedback
Discuss limitations, alternative explanations and next steps
Friday office hours: Friday, 18 December — final corrections, portfolio and documentation review, career pathways and next steps into research or advanced analytics.
Weekly project: Final deliverable: a portfolio-ready project containing SQL queries, an Excel workbook, a custom dashboard, a written research report and a presentation.
Finish with work you can show.
Your capstone combines SQL queries, an Excel workbook, a custom dashboard, a written research report and a presentation. You’ll also receive feedback on your documentation and portfolio.
