{"id":29908848,"url":"https://github.com/ryanga09/digitalent_fundamentaldatascience-selfpractice","last_synced_at":"2025-08-02T00:44:59.803Z","repository":{"id":301469374,"uuid":"1009356599","full_name":"RyanGA09/DigiTalent_FundamentalDataScience-SelfPractice","owner":"RyanGA09","description":"A repository of hands-on projects from DigiTalent’s Fundamental Data Science training, covering web scraping, data exploration, data cleaning, and data annotation. 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The focus topics include:\n\n- 🌐 Data Scraping\n  Learn how to acquire data from various web sources using automated tools.\n  Subtopics:\n\n  - What is Data?\n  - Data Collection Methods\n  - Data Scraping Tools\n  - Data Integrity \u0026 Ethics\n  - Hands-on Practice through the included self-practice exercises\n\n- 📈 Data Exploration\n  Analyze and understand the structure and patterns in your data.\n  Subtopics:\n\n  - Data Understanding\n  - Reviewing Dataset Structure\n  - Data Validation Techniques\n  - Hands-on Practice through the included self-practice exercises\n\n- 🧹 Data Cleansing\n  Clean and refine your dataset to ensure quality and reliability.\n  Subtopics:\n\n  - Data Cleaning Concepts\n  - Handling Missing \u0026 Duplicate Values\n  - Data Reduction Strategies\n  - Hands-on Practice through the included self-practice exercises\n\n- 🏷️ Data Annotation\n  Prepare labeled datasets for use in supervised machine learning tasks.\n  Subtopics:\n  - Defining Labels \u0026 Categories\n  - Data Annotation Techniques\n  - Manual \u0026 Assisted Labeling Tools\n  - Hands-on Practice through the included self-practice exercises\n\n## 🗂️ Repository Structure\n\n```bash\nDigiTalentPractice-FundamentalDataScience/\n├── data/                          # Contains raw/external datasets\n│   ├── Data_Nasabah.csv           # Local dataset\n│   └── train_prices.csv           # Kaggle dataset (not included in repo)\n│\n├── notebooks/                     # Jupyter notebooks\n│   ├── self_practice-1.ipynb\n│   ├── self_practice-2.ipynb\n│   ├── self_practice-3.ipynb\n│   └── self_practice-4.ipynb\n│\n├── requirements.txt               # Python dependencies\n├── README.md                      # Project overview and setup instructions\n└── .gitignore                     # Files/folders to exclude from version control\n\n```\n\n**⚠️ Note: data/train_prices.csv is downloaded via the Kaggle API and is not included in this repository. Make sure to download it manually before running related notebooks.**\n\n## 🚀 How to Use\n\n1. 📥 Clone this repository to your local machine:\n\n   ```bash\n   git clone https://github.com/RyanGA09/DigiTalentPractice-FundamentalDataScience.git\n   ```\n\n2. 📦 Install the environment (recommended to use venv or conda):\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n3. 📘 Open the notebook corresponding to the topic you want to learn and run the code cells sequentially.\n\n## 👨‍💻 Author\n\nRyan Gading Abdullah\n\n[![GitHub](https://img.shields.io/badge/GitHub-000000?style=for-the-badge\u0026logo=github\u0026logoColor=white)](https://github.com/RyanGA09)\n[![GitLab](https://img.shields.io/badge/GitLab-FC6D26?style=for-the-badge\u0026logo=gitlab\u0026logoColor=white)](https://gitlab.com/RyanGA09)\n[![Instagram](https://img.shields.io/badge/Instagram-E4405F?style=for-the-badge\u0026logo=instagram\u0026logoColor=white)](https://instagram.com/ryan_g._a)\n[![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge\u0026logo=linkedin\u0026logoColor=white)](https://www.linkedin.com/in/ryan-gading-abdullah/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fryanga09%2Fdigitalent_fundamentaldatascience-selfpractice","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fryanga09%2Fdigitalent_fundamentaldatascience-selfpractice","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fryanga09%2Fdigitalent_fundamentaldatascience-selfpractice/lists"}