The source code for the educational website Data Science is available in this repository. This website was developed for aspiring students who are interested in data science and it gives you access to resources, including courses, that can help you develop your abilities. To direct users to the desired area of the website, the website is made up of a number of different sections, including home, about, courses, FAQ, and contact. Students can sign up and begin their career as a data scientist.
This webpage is still under construction. I'm making this project open source so that if any one wants to contribute to this project, to make it easier for their fellow learners to grasp the concepts of data science, then genuinly you are welcome here :)
Project Purpose : Educational Startup related to Data Science
Project Website : Visit Here
Developer : Aniket Sinha
- Meet fellow coders, build a team.
- Get your questions answered and help others by answering theirs.
- Share your creative ideas about improving this community.
- Showcase you previous works as a motivation for others.
- Resources to get you started and sharpening the skills.
- And lot of things coming from you.
**Components of Website**
Landing Page
This is the initial page a user sees when the website is opened. The navigation bar on the website is divided into several areas, including about, courses, FAQ, and contact. Users can sign up on this website in order to keep track of their courses and learning progress. You have the choice to 'get started' in this area and start your data science adventure.
About Us
This section provides a quick explanation of what Data Science is along with a visual illustration of the fields that make up data science. This section also includes a representation of the number of courses offered, students enrolled, and prizes awarded.
Courses
The courses page offers a wide range of courses designed to equip you with the knowledge and skills needed to excel in the field of data science. Whether you're a beginner or an experienced professional, we have courses designed to meet your needs and help you stay ahead in this rapidly evolving field.
FAQ
The Frequently Asked Questions is dedicated towards providing answers to commonly asked questions. These questions aim at addressing the most common queries, offer insights, and provide clarity on various aspects of Data Science that a user could have.
Contact
Last but not least, the website includes information about how the user can get in touch via the provided phone number or email address. Users can use a variety of social media links to keep up with the most recent Data Science related news, announcements, events, and blog articles. It includes the website's privacy statement, terms & conditions, and return policy.
If you're not comfortable with command line, here are tutorials using GUI tools. If you don't have git on your machine, install it.
1. Fork this repository.
2. Clone your forked copy of the project.
git clone https://github.com/aniketsinha2002/DataScienceWebsite.github.io.git
3. Navigate to the project directory 📁 .
cd DataScienceWebsite.github.io.git
4. Add a reference(remote) to the original repository.
git remote add upstream https://github.com/aniketsinha2002/DataScienceWebsite.github.io.git
5. Check the remotes for this repository.
git remote -v
6. Always take a pull from the upstream repository to your master branch to keep it at par with the main project(updated repository).
git pull upstream main
7. Create a new branch.
git checkout -b <your_branch_name>
8. Perform your desired changes to the code base.
9. Track your changes:heavy_check_mark: .
git add .
10. Commit your changes .
git commit -m "Your message"
11. Push the committed changes in your feature branch to your remote repo.
git push -u origin <your_branch_name>
12. To create a pull request, click on compare and pull requests. Please ensure you compare your feature branch to the desired branch of the repository you are supposed to make a PR to.
13. Add appropriate title and description to your pull request explaining your changes and efforts done.
14. Click on Create Pull Request.
15. Congratulations! You have made a succsessful PR to the DataScienceWebsite.
16. Now sit back patiently and relax while your PR is being reviewed.
- Please follow best code formatting and linting practices to assure good code quality. You should use tools such as Prettier or Eslint for the purpose.
- GSSoC'23
