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Introduction to Data Science \u0026 workflow overview  \n2. Setting up environment (Anaconda, Jupyter, VS Code)  \n3. Python essentials (variables, loops, conditionals, functions, OOP)  \n4. Working with data structures — lists, dicts, tuples, sets  \n5. File handling (CSV, JSON, text files)  \n6. Libraries:  \n   - **NumPy** → numerical operations  \n   - **Pandas** → data manipulation \u0026 cleaning  \n   - **Matplotlib / Seaborn** → visualization  \n7. Handling missing values \u0026 preprocessing data  \n8. Exploratory Data Analysis (EDA)  \n9. SQL for data analysis  \n10. Probability, statistics, and hypothesis testing  \n11. Intro to Machine Learning — regression \u0026 classification  \n12. Model evaluation metrics  \n13. Git \u0026 GitHub for version control  \n14. Real-world case studies \u0026 project work  \n\n\u003e ⚙️ *Note: Course structure may evolve; this list is based on currently advertised content.*\n\n---\n\n## 🛠️ Technologies \u0026 Tools Explored  \n\n- **Programming Languages:** ![Python](https://img.shields.io/badge/Python-3.11-blue?logo=python\u0026logoColor=white)\n- **Anaconda:** ![Anaconda](https://img.shields.io/badge/Anaconda-2023-green?logo=anaconda\u0026logoColor=white)\n- **Data Analysis \u0026 Manipulation:** ![Pandas](https://img.shields.io/badge/Pandas-1.6-blue?logo=pandas\u0026logoColor=white), ![NumPy](https://img.shields.io/badge/NumPy-1.26-blue?logo=numpy\u0026logoColor=white)\n- **Visualization:** Matplotlib, Seaborn ![Matplotlib](https://img.shields.io/badge/Matplotlib-3.7-orange?logo=matplotlib\u0026logoColor=white)\n- **Machine Learning:** Scikit-learn  ![Scikit-learn](https://img.shields.io/badge/Scikit--learn-1.2-green?logo=scikit-learn\u0026logoColor=white) \n- **Environment:** Jupyter Notebook, Anaconda ![Jupyter](https://img.shields.io/badge/Jupyter-orange?logo=jupyter\u0026logoColor=white)\n- **Version Control:** Git \u0026 GitHub  ![Git](https://img.shields.io/badge/Git-F05032?logo=git\u0026logoColor=white), ![GitHub](https://img.shields.io/badge/GitHub-181717?logo=github\u0026logoColor=white)\n\n---\n\n## 🚀 How to Use This Repository  \n\n1. **Clone the repo**  \n   ```bash\n   git clone https://github.com/sidraanl-08/completedatascience.git\n\n\n## 🙏 Credits \u0026 Acknowledgments\n\nMassive thanks to CodeWithHarry for his exceptional teaching and clear explanation!\nThis repository and my learning journey would not have been possible without his guidance.\n\n🔗 Official Links\n\nWebsite: https://www.codewithharry.com\n\nYouTube: CodeWithHarry\n\nInstagram: @codewithharry\n\n🎓 All course content, guidance, and teaching methodology belong to CodeWithHarry.\n\n\n📘 This repository is part of my personal learning journey.\nFeel free to explore, fork, and learn along!\n\nMade with ❤️ by Sidraa \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsidraanl-08%2Fcompletedatascience","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsidraanl-08%2Fcompletedatascience","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsidraanl-08%2Fcompletedatascience/lists"}