Learning Notes

This repository contains organized notes, code snippets, and summaries from courses, tutorials, and hands-on experiments in Python, SQL, data analytics, algorithms, and AI. The goal is to maintain a structured knowledge base that consolidates concepts learned across multiple platforms and resources.

Structure

# Learning Notes

This repository contains organized notes, code snippets, and summaries from courses, tutorials, and hands-on experiments in **Python, SQL, data analytics, algorithms, and AI**.

The goal is to maintain a structured knowledge base that consolidates concepts learned across multiple platforms and resources.

---

## Sources

- datacamp  
- codecademy  
- educative  
- edX  
- ibm 
- nebius
- clickstream


## Structure

```text

learning-notes/
│
├── README.md
│
├── courses/
│   ├── datacamp/
│   │   ├── sql_fundamentals.md
│   │   └── python_data_analysis.md
│   │
│   ├── codecademy/
│   │   └── python_course_notes.md
│   │
│   ├── educative/
│   │   └── algorithm_patterns.md
│   │
│   ├── edx/
│   │   └── data_science_course_notes.md
│   │
│   ├── ibm/
│   │   └── data_science_course.md
│   │
│   ├── ibm/
│       └── data_science_course.md
│
│
├── ai-learning/
│   ├── llm_basics.md
│   ├── prompt_engineering.md
│   └── vector_databases.md
│
├── tools/
│   ├── git_notes.md
│   ├── docker_notes.md
│   └── workflow_tools.md
│
├── snippets/
│   ├── python_examples.py
│   ├── sql_patterns.sql
│   └── pandas_examples.py
│
└── concepts/
    ├── big_o_cheatsheet.md
    ├── data_pipeline_concepts.md
    └── ml_workflow.md

---

Topics Covered

Programming

• Python fundamentals
• Data structures and algorithms
• Code patterns and best practices

Data Analytics

• SQL querying
• Data analysis with Pandas
• Data visualization techniques

Artificial Intelligence

• Large language models (LLMs)
• Prompt engineering
• AI tools and workflows

Tools and Technologies

• Git and version control
• Data processing workflows
• Development tools

---

Learning Sources

Notes and examples in this repository are derived from courses and materials from platforms such as:

• DataCamp
• Codecademy
• Educative
• edX
• IBM learning resources
• Other technical tutorials and experiments

---

Purpose

This repository serves as a personal knowledge base to:

• consolidate learning from multiple courses
• document key concepts and insights
• maintain reusable code snippets
• track progress in data, software, and AI topics

---

License

This project is licensed under the MIT License.