# mragpavank/data-science-materials-useful-for-all-data-science-professionals architecture

> Architecture diagram of the GitHub repository mragpavank/data-science-materials-useful-for-all-data-science-professionals, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-27). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals
- Repository: https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals

## Overview

This repository is a collection of educational materials for learning data science and related topics. The principal workflow is a learner choosing and studying a resource directly; the README describes educational use but does not document an application or an ordered curriculum. The graph groups representative materials by subject, not by a claimed sequence. The flat file tree and lack of source excerpts provide no evidence for further runtime relationships.

Main entry points: [`Python manual.pdf`](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Python%20manual.pdf) (Python manual), [`STATISTICS for Data science.pdf`](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/STATISTICS%20for%20Data%20science.pdf) (Statistics for data science), [`SQL technical concepts.pdf`](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/SQL%20technical%20concepts.pdf) (SQL concepts), [`Introducion to Data analysis.pdf`](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Introducion%20to%20Data%20analysis.pdf) (Data analysis introduction)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_foundations["Programming & statistics"]
  node_python["Python manual<br/>[Python manual.pdf]"]
  node_statistics["Statistics for data science"]
  node_sql["SQL concepts"]
end

subgraph group_data["Data analysis"]
  node_intro_analysis["Data analysis introduction"]
  node_pandas["Learning pandas"]
  node_cleaning["Data cleaning<br/>[Data cleaning.pdf]"]
  node_visualization["Data visualization"]
  node_analytics["Analytics guide"]
end

subgraph group_ml["Machine learning &amp; AI"]
  node_ml_basics["ML basics<br/>[ML Basics.pdf]"]
  node_pipelines["ML pipelines"]
  node_deep_learning["Deep learning<br/>[Deep learning.pdf]"]
  node_nlp["NLP<br/>[NLP.pdf]"]
  node_mlops["MLOps<br/>[MLOps.pdf]"]
end

subgraph group_practice["Projects &amp; careers"]
  node_projects["Data science projects"]
  node_roadmap["Data analyst roadmap"]
  node_interviews["Data science interview questions"]
  node_resources["Data science resources<br/>[README.md]"]
end

node_learner(("Learner"))

node_learner -->|"studies"| node_python
node_learner -->|"studies"| node_statistics
node_learner -->|"studies"| node_sql
node_learner -->|"studies"| node_intro_analysis
node_learner -->|"studies"| node_pandas
node_learner -->|"studies"| node_cleaning
node_learner -->|"studies"| node_visualization
node_learner -->|"studies"| node_analytics
node_learner -->|"studies"| node_ml_basics
node_learner -->|"studies"| node_pipelines
node_learner -->|"studies"| node_deep_learning
node_learner -->|"studies"| node_nlp
node_learner -->|"studies"| node_mlops
node_learner -->|"studies"| node_projects
node_learner -->|"studies"| node_roadmap
node_learner -->|"studies"| node_interviews
node_learner -->|"checks purpose"| node_resources

click node_python "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Python%20manual.pdf"
click node_statistics "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/STATISTICS%20for%20Data%20science.pdf"
click node_sql "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/SQL%20technical%20concepts.pdf"
click node_intro_analysis "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Introducion%20to%20Data%20analysis.pdf"
click node_pandas "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Learning%20pandas.pdf"
click node_cleaning "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Data%20cleaning.pdf"
click node_visualization "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Principle%20of%20data%20visualization.pdf"
click node_analytics "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Analytics%20guide.pdf"
click node_ml_basics "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/ML%20Basics.pdf"
click node_pipelines "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Machine%20learning%20Pipelines.pdf"
click node_deep_learning "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Deep%20learning.pdf"
click node_nlp "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/NLP.pdf"
click node_mlops "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/MLOps.pdf"
click node_projects "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Data%20Science%20Projectss-Ideas%20from%20Krish%20Naik.pdf"
click node_roadmap "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Data%20Analyst%20Roadmap.pdf"
click node_interviews "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Data%20science%20Interview%20questions.pdf"
click node_resources "https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/README.md"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_python,node_statistics,node_sql toneBlue
class node_intro_analysis,node_pandas,node_cleaning,node_visualization,node_analytics toneAmber
class node_ml_basics,node_pipelines,node_deep_learning,node_nlp,node_mlops toneMint
class node_projects,node_roadmap,node_interviews,node_resources toneRose
class node_learner toneIndigo
```

## Components

### Programming & statistics

- [Python manual](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Python%20manual.pdf): `Python manual.pdf`
- [Statistics for data science](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/STATISTICS%20for%20Data%20science.pdf): `STATISTICS for Data science.pdf`
- [SQL concepts](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/SQL%20technical%20concepts.pdf): `SQL technical concepts.pdf`

### Data analysis

- [Data analysis introduction](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Introducion%20to%20Data%20analysis.pdf): `Introducion to Data analysis.pdf`
- [Learning pandas](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Learning%20pandas.pdf): `Learning pandas.pdf`
- [Data cleaning](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Data%20cleaning.pdf): `Data cleaning.pdf`
- [Data visualization](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Principle%20of%20data%20visualization.pdf): `Principle of data visualization.pdf`
- [Analytics guide](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Analytics%20guide.pdf): `Analytics guide.pdf`

### Machine learning & AI

- [ML basics](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/ML%20Basics.pdf): `ML Basics.pdf`
- [ML pipelines](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Machine%20learning%20Pipelines.pdf): `Machine learning Pipelines.pdf`
- [Deep learning](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Deep%20learning.pdf): `Deep learning.pdf`
- [NLP](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/NLP.pdf): `NLP.pdf`
- [MLOps](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/MLOps.pdf): `MLOps.pdf`

### Projects & careers

- [Data science projects](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Data%20Science%20Projectss-Ideas%20from%20Krish%20Naik.pdf): `Data Science Projectss-Ideas from Krish Naik.pdf`
- [Data analyst roadmap](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Data%20Analyst%20Roadmap.pdf): `Data Analyst Roadmap.pdf`
- [Data science interview questions](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/Data%20science%20Interview%20questions.pdf): `Data science Interview questions.pdf`
- [Data science resources](https://github.com/mragpavank/data-science-materials-useful-for-all-data-science-professionals/blob/main/README.md): `README.md`

### Other components

- **Learner**

## Connections

- Learner → Python manual: studies
- Learner → Statistics for data science: studies
- Learner → SQL concepts: studies
- Learner → Data analysis introduction: studies
- Learner → Learning pandas: studies
- Learner → Data cleaning: studies
- Learner → Data visualization: studies
- Learner → Analytics guide: studies
- Learner → ML basics: studies
- Learner → ML pipelines: studies
- Learner → Deep learning: studies
- Learner → NLP: studies
- Learner → MLOps: studies
- Learner → Data science projects: studies
- Learner → Data analyst roadmap: studies
- Learner → Data science interview questions: studies
- Learner → Data science resources: checks purpose