KDnuggets Complete Collection of Data Science Cheat Sheets
Type: Curated Reference Collection
Author: Abid Ali Awan
Published: March 2022 (KDnuggets)
Pages: 17
URL: https://www.kdnuggets.com/2022/03/complete-collection-data-science-cheat-sheets.html
What This Document Is
A curated catalog of data science cheat sheets organized into 12 thematic categories, published by KDnuggets (Data Science community platform). The PDF itself is a guide/introduction listing — it does not contain the actual cheat sheet pages, but references and links to individual cheat sheets maintained across the web.
Author context: Abid Ali Awan (@1abidaliawan) is a certified data scientist and writer at KDnuggets, specializing in machine learning content creation.
Key Categories
| # | Category | Cheat Sheets | RegenNeighbourhood Mapping |
|---|---|---|---|
| 1 | SQL | 4 sheets | Community metrics storage & queries |
| 2 | Web Scraping | 7 sheets | Open-source data acquisition for community research |
| 3 | Statistics, Probability & Math | 9 sheets | Sensor data interpretation, probabilistic reasoning |
| 4 | Data Analytics | Python (9), R (14), Julia (5) | Household/neighbourhood behavioral analytics |
| 5 | Business Intelligence | 6 sheets | Dashboard design for shared governance metrics |
| 6 | Big Data | 5 sheets | Shared infrastructure data processing at scale |
| 7 | Data Structures & Algorithms | 5 sheets | Sensor pipeline efficiency, edge computing |
| 8 | Machine Learning | 9 sheets | IoT predictive maintenance, resource forecasting |
| 9 | Deep Learning | 9 sheets | Image/signal processing for land monitoring |
| 10 | Natural Language Processing | 9 sheets | Governance communication analysis, collective sensemaking |
| 11 | Data Engineering | 9 sheets | Sensor pipeline architecture, automated data flows |
| 12 | Web Frameworks | 7 sheets | Sharing data products via lightweight web apps |
| — | VIP Bonus | 5 sheets | Rapid interview preparation |
Total cheat sheet references: 100+
AI Skills Relevance
The collection maps directly to the NVIDIA Data Science certification curriculum:
- SQL → DAX100: Fundamentals of SQL
- Data Analytics (Python/R) → DAA150: Data Analytics with Python
- Machine Learning → MLE100: Machine Learning Fundamentals
- Deep Learning → DLI100: Deep Learning Fundamentals
- Big Data → BDE200: Big Data Engineering
- Data Engineering → DE100: Data Engineering Fundamentals
Proposed learning pathway: RegenTribe members can use this collection alongside NVIDIA certs to build structured data science competency.
RegenNeighbourhood Application Areas
- Community Metrics: SQL + Business Intelligence for shared KPIs (energy use, water, food production)
- Sensor Pipelines: Data Engineering + Big Data for IoT toolkit data flows
- Predictive Maintenance: Machine Learning for water tank / soil moisture alert systems
- Communication Analysis: NLP for governance meeting summarization and collective decision tracking
- Edge Computing: Data Structures & Algorithms for HP edge node efficiency
- Lightweight Data Products: Web Frameworks (Streamlit, FastAPI) for sharing visualizations with neighbourhood members
Notes
- This PDF is a catalog, not the actual cheat sheet content. Individual sheets live at various URLs (KDnuggets, GitHub, official docs).
- The collection was last indexed March 2022 — some URLs may have moved.
- Julia section positions this language as “the future of data science” — relevant for members exploring high-performance scientific computing on constrained hardware (Raspberry Pi, edge nodes).
Captured: 2026-05-08
Source: RegenTribe / Genesis Knowledge Graph
Related
- No related pages yet.