This repository contains a curated collection of data science projects completed on DataCamp, each exploring different domains, techniques, and datasets using Python and related technologies.
Below is a list of the projects included in this repository, each located in its own directory:
Builds and trains deep learning models to recognize American Sign Language gestures from image data.
Performs data analysis on crime datasets from Los Angeles to uncover patterns and trends.
Examines survey data to understand factors affecting students' mental health.
Demonstrates ETL and pipeline engineering for retail transaction datasets.
Uses audio features and machine learning to classify music tracks by genre.
Applies clustering algorithms to biological data to distinguish penguin species.
Analyzes and visualizes public transport data for London, including journeys and network structure.
- Key files:
- notebook.ipynb: Main analysis and visualization notebook.
- tfl_journeys_final.csv: Dataset of journeys.
- london.jpg, tube.jpg: Visual assets.
Investigates the development history and community aspects of the Linux operating system.
Performs exploratory data analysis on Netflix movie offerings and characteristics.
Showcases code review practices and automated quality checks on a sample project.
Develops machine learning models to predict agricultural outcomes from environmental data.
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Clone the repository:
git clone https://github.com/alyalsayed/Datacamp_Projects.git
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Explore each project folder: Each directory contains code, datasets, and (where available) notebooks or documentation for running the analyses.
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Dependencies: Most projects use Python (Jupyter notebooks), and may require libraries like pandas, numpy, matplotlib, scikit-learn, etc. Refer to any
requirements.txtor notebook instructions per project.
This repository is released under the MIT License.
Created by alyalsayed.
Explore, learn, and build your data science skills with real projects!