Learning Hub
Try This First
Test your knowledge before reading. Don't worry if you get it wrong — that's part of learning.
Key Insights
- Interactive lessons, quizzes, and tutorials on AML, financial markets, and science.
The Learning Hub is your gateway to structured, self-paced lessons across all three AcaciaFund pillars: AML, Markets, and Data Engineering.
Each lesson combines:
- Bloom-graded content — from Remember (flashcards, definitions) through Evaluate (rubric-based assessment) and Create (synthesis challenges)
- Interactive quizzes — multiple-choice and open-ended questions with instant feedback
- Reading streak tracking — your progress is saved locally and builds a visible streak (🔥 ≥7 days, ✨ ≥3, 📖 1–2)
- Flashcard decks — flip-to-reveal terminology for each pillar
The 15 lessons span three difficulty levels:
- 🌱 Beginner — AML Basics, Quiz: AML Compliance, DataOps Introduction, Data Engineering Foundations
- 📘 Intermediate — Market Analysis, Data Quality Engineering, Open-Source Data Stack, Crypto AML, Semiconductor Supply Chain, CRISPR Gene Editing, Behavioral Design, Trade-Based ML Sanctions, Behavioral Finance Portfolio, Meta-Analysis Statistics
- 🔥 Advanced — Data Ethics & Privacy
Start with the AML Basics lesson if you are new, or pick any topic that matches your interest. Each lesson takes 5–15 minutes to complete.
How to Use This Hub: A Bloom Framework
Each lesson includes questions at multiple Bloom taxonomy levels. Here is how to get the most out of each level:
Apply (L3) — Worked Example
When a lesson asks "How can these findings be applied?", try this three-step framework:
- Identify the mechanism — What core principle or relationship does the synthesis establish? (e.g., "ML model accuracy depends on feature diversity")
- Find a concrete context — Which real-world scenario tests this principle? (e.g., "A compliance team screening cross-border payments with limited counterparty data")
- Trace the outcome — Apply the principle step by step. What changes? What trade-offs emerge? What would you measure?
Analyse (L4) — Cross-Pillar Protocol
When asked to "analyse underlying assumptions", use the cross-pillar lens:
- Source decomposition — Separate the claim from its source. Is the source from a different pillar? A Markets claim applied to AML may carry hidden assumptions about liquidity vs. compliance time horizons.
- Bias audit — Check for three common biases: recency (overweighting new events), availability (overweighting vivid examples), and confirmation (selecting evidence that fits the pillar narrative).
- Counterfactual test — If the core assumption were reversed, would the conclusion still hold?
Evaluate (L5) — SQI-Based Rubric
When asked to "evaluate the strength of evidence", use this rubric:
- SQI >= 0.70: Strong — multiple high-authority sources agree, fresh, cross-validated across pillars.
- SQI 0.50–0.69: Moderate — some disagreement or thin source diversity; treat conclusions as provisional.
- SQI < 0.50: Weak — limited sources or low authority; identify which specific sources drive the score and whether they are credible.
Create (L6) — Synthesis Challenge Template
To create your own synthesis from multiple sources:
- Harvest — Collect 5+ sources from at least 2 pillars on a single question.
- Weight — Rank by authority (primary research > regulatory filings > news > opinion).
- Synthesise — Write a 3-paragraph summary: (1) what is known, (2) where sources disagree, (3) what is unknown.
- Grade yourself — Does your synthesis pass at each Bloom level? If not, which level needs more evidence?
Return to this framework whenever you encounter an open-ended question. The goal is not a "correct" answer but a reasoned one — supported by the same SQI metrics the platform uses.
Article Metadata
Review with Spaced Repetition
Add this lesson's 3 flashcards to your SM-2 study queue. They will appear when due in the Study Queue.
Feynman Concept Cards
Master each building block: read the ELI5, explore the analogy, work the example, find your gaps, teach it back, build it.
Semiconductor Industry is a concept in industry analysis. In simple terms, Semiconductor Industry covers industry analysis in Markets. This markets concept addresses key topics in the industry analysis in markets domain. Also known as: chip industry, semiconductor supply cha
Analogy
Example
Find Gaps
Explain Semiconductor Industry as if teaching a colleague who is new to industry analysis. Cover: what it is, how it works, and why it matters.
Create
Create a diagram that demonstrates Semiconductor Industry in a real-world industry analysis scenario. Walk through your design decisions.
Show solution
A diagram for Semiconductor Industry should include: 1. The core components of semiconductor industry 2. How they interact 3. Expected outcomes or outputs
Data Quality is a concept in best practices. In simple terms, Data Quality covers best practices in Data Engineering. This data engineering concept addresses key topics in the best practices in data engineering domain. Also known as: data observability, data val
Analogy
Example
Find Gaps
Explain Data Quality as if teaching a colleague who is new to best practices. Cover: what it is, how it works, and why it matters.
Create
Create a checklist that demonstrates Data Quality in a real-world best practices scenario. Walk through your design decisions.
Show solution
A checklist for Data Quality should include: 1. The core components of data quality 2. How they interact 3. Expected outcomes or outputs
DataOps is a concept in best practices. In simple terms, DataOps covers best practices in Data Engineering. This data engineering concept addresses key topics in the best practices in data engineering domain. Also known as: DataOps practices, data operation
Analogy
Example
Find Gaps
Explain DataOps as if teaching a colleague who is new to best practices. Cover: what it is, how it works, and why it matters.
Create
Create a checklist that demonstrates DataOps in a real-world best practices scenario. Walk through your design decisions.
Show solution
A checklist for DataOps should include: 1. The core components of dataops 2. How they interact 3. Expected outcomes or outputs
MiCA — Markets in Crypto-Assets Regulation is a concept in crypto aml. In simple terms, MiCA — Markets in Crypto-Assets Regulation covers crypto compliance within Compliance. This compliance concept addresses key topics in the crypto compliance within compliance domain. Also known as: Mi
Analogy
Example
Find Gaps
Explain MiCA — Markets in Crypto-Assets Regulation as if teaching a colleague who is new to crypto aml. Cover: what it is, how it works, and why it matters.
Create
Create a diagram that demonstrates MiCA — Markets in Crypto-Assets Regulation in a real-world crypto aml scenario. Walk through your design decisions.
Show solution
A diagram for MiCA — Markets in Crypto-Assets Regulation should include: 1. The core components of mica crypto assets 2. How they interact 3. Expected outcomes or outputs
Market Microstructure is a concept in foundations. In simple terms, Market Microstructure covers foundational knowledge in Markets. This markets concept addresses key topics in the foundational knowledge in markets domain. Also known as: microstructure. Related concep
Analogy
Example
Find Gaps
Explain Market Microstructure as if teaching a colleague who is new to foundations. Cover: what it is, how it works, and why it matters.
Create
Create a diagram that demonstrates Market Microstructure in a real-world foundations scenario. Walk through your design decisions.
Show solution
A diagram for Market Microstructure should include: 1. The core components of market microstructure 2. How they interact 3. Expected outcomes or outputs
Feynman Synthesis — Prove You Understand
1. The One-Pager
Explain this lesson's core idea to a smart 15-year-old. No jargon allowed.
2. The Gap Map
List 3 things you are still unsure about. Be specific.
Knowledge Check
Test your understanding of this lesson.
Flashcards
Space = flip · 1-4 = grade · Swipe on mobile