Welcome to the Data Angels Resource Guide! This repository is designed to empower and equip both new and experienced data professionals with a set of resources covering various aspects of data science, data engineering, and analytics. Whether you're looking to sharpen your technical skills, explore data career paths, or figure out your options in data-related fields, this guide aims to support your journey. Our collective knowledge and contributions can help shape a promising future in the data domain.
Resources and tools to help you understand how to analyze data effectively. This includes statistical methods, visualization techniques, and case studies showcasing real-world analytics.
Essential knowledge and tools for building robust data pipelines and architectures. Learn about databases, big data technologies, ETL processes, and data warehousing.
Guides on designing and implementing reliable experiments in a data-driven environment. Learn about A/B testing, multivariate testing, and the statistical principles behind experimental design.
Tutorials, courses, and projects related to machine learning and predictive modeling. This includes both supervised and unsupervised learning techniques, model evaluation, and deployment.
Advice on navigating the data career landscape, including job roles, skill development, and industry trends. Insights into what it takes to grow from an entry-level position to a leadership role.
Information about pursuing certificates, bootcamps, online programs, or graduate studies in data-related fields, including choosing the right program, application tips, and the benefits of advanced education in data science.
We welcome contributions from everyone who wishes to add valuable resources to this repository. Here’s how you can contribute:
Start by forking the repository to your GitHub account. This creates a copy of the repository under your account, allowing you to make changes without affecting the original repository.
Click on the 'Fork' button at the top-right of this repository page on GitHub.Clone the forked repository to your local machine. Replace YOUR-USERNAME with your GitHub username.
git clone https://github.com/YOUR-USERNAME/data-professional-resource-guide.git
cd data-professional-resource-guideCreate a new branch for your contributions. It’s a good practice to name the branch related to the type of contribution you’re making.
git checkout -b branch-nameAdd your resources to the relevant section/category in the README.md file or add new files to the dubfolder if necessary. Make sure to follow any existing format or style guidelines.
After adding your resources, commit the changes with a clear, descriptive message.
git add .
git commit -m "Add detailed description of your changes"Push the changes back to your GitHub repository.
git push origin branch-nameGo to your repository on GitHub and click ‘New Pull Request’. Select the main branch of the original repository and your new branch. Submit the pull request with a description of your contributions.
Make sure to provide a detailed description of what changes you've made and why they are beneficial.Maintainers of the repository will review your pull request. After the review, your contributions may be merged into the main branch, making them available to all users.
Your feedback is important to help us improve this resource guide. If you have suggestions or feedback, please open an issue in this repository, and we will look into it promptly.
Thank you for contributing to the Data Angels Resource Guide!