1st Principles

Subject

Data Science

Questions, data collection, and models that support decisions under uncertainty.

101 sub-topics · use search below on large subjects

Topics

Foundations

Orientation and shared vocabulary for this subject.

Application

Constraints in real jobs (Science)

Constraints in real jobs as it applies to Data Science.

Cost and benefit (Science)

Cost and benefit as it applies to Data Science.

Failure modes (Science)

Failure modes as it applies to Data Science.

Implementation steps (Science)

Implementation steps as it applies to Data Science.

Maintenance over time (Science)

Maintenance over time as it applies to Data Science.

Problem framing (Science)

Problem framing as it applies to Data Science.

Risk (Science)

Risk as it applies to Data Science.

Scaling up (Science)

Scaling up as it applies to Data Science.

Stakeholders (Science)

Stakeholders as it applies to Data Science.

Trade-offs (Science)

Trade-offs as it applies to Data Science.

Communication

Cross-disciplinary talk (Science)

Cross-disciplinary talk as it applies to Data Science.

Explaining to beginners (Science)

Explaining to beginners as it applies to Data Science.

Media coverage (Science)

Media coverage as it applies to Data Science.

Open questions (Science)

Open questions as it applies to Data Science.

Policy briefs (Science)

Policy briefs as it applies to Data Science.

Presentations (Science)

Presentations as it applies to Data Science.

Public controversy (Science)

Public controversy as it applies to Data Science.

Teaching others (Science)

Teaching others as it applies to Data Science.

Visuals that teach (Science)

Visuals that teach as it applies to Data Science.

Writing clear summaries (Science)

Writing clear summaries as it applies to Data Science.

Comparison

Analogies from other fields (Science)

Analogies from other fields as it applies to Data Science.

Common confusions (Science)

Common confusions as it applies to Data Science.

Competing models (Science)

Competing models as it applies to Data Science.

Consensus areas (Science)

Consensus areas as it applies to Data Science.

Debates that matter (Science)

Debates that matter as it applies to Data Science.

Historical shifts (Science)

Historical shifts as it applies to Data Science.

Interdisciplinary links (Science)

Interdisciplinary links as it applies to Data Science.

Regional differences (Science)

Regional differences as it applies to Data Science.

Schools of thought (Science)

Schools of thought as it applies to Data Science.

Translation of terms (Science)

Translation of terms as it applies to Data Science.

Context

Climate and environment (Science)

Climate and environment as it applies to Data Science.

Demographics (Science)

Demographics as it applies to Data Science.

Equity and access (Science)

Equity and access as it applies to Data Science.

Funding (Science)

Funding as it applies to Data Science.

Future scenarios (Science)

Future scenarios as it applies to Data Science.

Global trends (Science)

Global trends as it applies to Data Science.

Institutions (Science)

Institutions as it applies to Data Science.

Regulation (Science)

Regulation as it applies to Data Science.

Social impact (Science)

Social impact as it applies to Data Science.

Technology change (Science)

Technology change as it applies to Data Science.

Core ideas

Abstraction levels (Science)

Abstraction levels as it applies to Data Science.

Cause and correlation (Science)

Cause and correlation as it applies to Data Science.

Central definitions (Science)

Central definitions as it applies to Data Science.

Equilibrium and change (Science)

Equilibrium and change as it applies to Data Science.

Feedback loops (Science)

Feedback loops as it applies to Data Science.

Laws, rules, or patterns (Science)

Laws, rules, or patterns as it applies to Data Science.

Models and diagrams (Science)

Models and diagrams as it applies to Data Science.

Scale: micro to macro (Science)

Scale: micro to macro as it applies to Data Science.

Systems and parts (Science)

Systems and parts as it applies to Data Science.

Units and measurement (Science)

Units and measurement as it applies to Data Science.

Deep dives

Advanced preview (Science)

Advanced preview as it applies to Data Science.

Capstone directions (Science)

Capstone directions as it applies to Data Science.

Classic papers or texts (Science)

Classic papers or texts as it applies to Data Science.

Edge cases (Science)

Edge cases as it applies to Data Science.

Landmark discoveries (Science)

Landmark discoveries as it applies to Data Science.

Minority reports (Science)

Minority reports as it applies to Data Science.

Open research fronts (Science)

Open research fronts as it applies to Data Science.

Paradigm shifts (Science)

Paradigm shifts as it applies to Data Science.

Synthesis projects (Science)

Synthesis projects as it applies to Data Science.

Where to go next (Science)

Where to go next as it applies to Data Science.

Evidence

Anomalies (Science)

Anomalies as it applies to Data Science.

Bias and blind spots (Science)

Bias and blind spots as it applies to Data Science.

Case studies (Science)

Case studies as it applies to Data Science.

Conflicting studies (Science)

Conflicting studies as it applies to Data Science.

Data tables and charts (Science)

Data tables and charts as it applies to Data Science.

Primary sources (Science)

Primary sources as it applies to Data Science.

Secondary summaries (Science)

Secondary summaries as it applies to Data Science.

Strong versus weak claims (Science)

Strong versus weak claims as it applies to Data Science.

Triangulation (Science)

Triangulation as it applies to Data Science.

Uncertainty language (Science)

Uncertainty language as it applies to Data Science.

Methods

Documentation (Science)

Documentation as it applies to Data Science.

Estimation and error (Science)

Estimation and error as it applies to Data Science.

Ethics in method (Science)

Ethics in method as it applies to Data Science.

Experiments and controls (Science)

Experiments and controls as it applies to Data Science.

Observation protocols (Science)

Observation protocols as it applies to Data Science.

Peer review (Science)

Peer review as it applies to Data Science.

Replication (Science)

Replication as it applies to Data Science.

Reproducible workflows (Science)

Reproducible workflows as it applies to Data Science.

Simulation and models (Science)

Simulation and models as it applies to Data Science.

Surveys and samples (Science)

Surveys and samples as it applies to Data Science.

Orientation

Careers and roles (Science)

Careers and roles as it applies to Data Science.

Everyday examples (Science)

Everyday examples as it applies to Data Science.

History in one glance (Science)

History in one glance as it applies to Data Science.

How claims get checked (Science)

How claims get checked as it applies to Data Science.

Jargon worth learning first (Science)

Jargon worth learning first as it applies to Data Science.

Objects you study (Science)

Objects you study as it applies to Data Science.

Reading habits that stick (Science)

Reading habits that stick as it applies to Data Science.

Tools practitioners use (Science)

Tools practitioners use as it applies to Data Science.

What questions the field asks (Science)

What questions the field asks as it applies to Data Science.

What the field is not (Science)

What the field is not as it applies to Data Science.

Skills

Checklists (Science)

Checklists as it applies to Data Science.

Collaboration norms (Science)

Collaboration norms as it applies to Data Science.

Debugging mistakes (Science)

Debugging mistakes as it applies to Data Science.

Hands-on practice (Science)

Hands-on practice as it applies to Data Science.

Mentorship (Science)

Mentorship as it applies to Data Science.

Pattern recognition (Science)

Pattern recognition as it applies to Data Science.

Portfolio pieces (Science)

Portfolio pieces as it applies to Data Science.

Self-assessment (Science)

Self-assessment as it applies to Data Science.

Speed versus accuracy (Science)

Speed versus accuracy as it applies to Data Science.

Tooling basics (Science)

Tooling basics as it applies to Data Science.