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https://github.com/syedfaiqueali/the-sparks-foundation
Data Science and Business Analytics Tasks
https://github.com/syedfaiqueali/the-sparks-foundation
data-science dataanalysis sparksfoundation-intern
Last synced: 8 days ago
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Data Science and Business Analytics Tasks
- Host: GitHub
- URL: https://github.com/syedfaiqueali/the-sparks-foundation
- Owner: syedfaiqueali
- License: mit
- Created: 2021-09-02T15:39:00.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2021-09-21T14:45:15.000Z (about 3 years ago)
- Last Synced: 2024-10-08T19:41:30.364Z (30 days ago)
- Topics: data-science, dataanalysis, sparksfoundation-intern
- Language: Jupyter Notebook
- Homepage:
- Size: 5.46 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
The Sparks Foundation
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In this I'm structuring tasks that I completed while working as an intern for [The Sparks Foundation.](https://www.thesparksfoundationsingapore.org/)
- **Internship Category** - Data Science and Business Analytics
- **Internship Duration** - 1 Month (September Batch - 2021)
- **Internship Type** - Work from Home
[
](https://www.youtube.com/watch?v=ksq0CL4ZrC4)
[
](https://github.com/faiqueali017/The-Sparks-Foundation/blob/main/Task_1%20Prediction%20Using%20Supervised%20ML/Task_1%20Prediction%20Using%20Supervised%20ML.ipynb)
### # Task-1 : Prediction using Supervised ML (Level - Beginner)
_Please click on the images on right side to view my solution._
1. Predict the percentage of marks of an student based on the number of study hours.
1. This is a simple linear regression task as it involves just 2 variables.
1. Data can be found at [http://bit.ly/w](http://bit.ly/w)
1. You can use R, Python, SAS Enterprise Miner or any other tool.
1. What will be predicted score if a student studies for 9.25 hrs/ day?
[](https://www.youtube.com/watch?v=MOUPQbLD6NE)
[](https://github.com/faiqueali017/The-Sparks-Foundation/blob/main/Task_2%20Prediction%20Using%20Unsupervised%20ML/Task_2%20Prediction%20Using%20Unsupervised%20ML.ipynb)
### # Task-2 : Prediction using Unsupervised ML (Level - Beginner)
_Please click on the images on right side to view my solution._
1. From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.
1. Use R or Python or perform this task.
1. Data can be found at [https://bit.ly/3cGyP8j](https://bit.ly/3cGyP8j)
[](https://www.youtube.com/watch?v=4WJdYu0Ku8U)
[](https://github.com/faiqueali017/The-Sparks-Foundation)
### # Task-3 : To Explore Business Analytics (Level - Beginner & Intermediate)
_Please click on the images on right side to view my solution (preferably youtube)._
1. Perform ‘Exploratory Data Analysis’ on the provided dataset ‘SampleSuperstore’
1. As a business manager, try to find out the weak areas where you can work to make more profit.
1. What all business problems you can derive by exploring the data?
1. You can choose any of the tool of your choice (Python/R/Tableau/PowerBI/Excel)
1. Dataset link :[https://bit.ly/3i4rbWl](https://bit.ly/3i4rbWl)
1. Create storyboards. Screen record along with your audio explaining the charts and interpretations.
[](https://www.youtube.com/watch?v=4DvtC89U5Kc)
[](https://github.com/faiqueali017/The-Sparks-Foundation)
### # Task-4 : To Explore Security/Defence Analytics (Level - Intermediate)
_Please click on the images on right side to view my solution (preferably youtube)._
1. Perform ‘Exploratory Data Analysis’ on the provided dataset ‘Global Terrorism’
1. As a security/defence analyst, try to find out the hot zone of terrorism.
1. What all security issues and insights you can derive by EDA?
1. You can choose any of the tool of your choice (Python/R/Tableau/PowerBI/Excel)
1. Dataset link :[https://bit.ly/2TK5Xn5](https://bit.ly/2TK5Xn5)
1. Create storyboards. Screen record along with your audio explaining the charts and interpretations.
[](https://www.youtube.com/watch?v=RbqaQunOJTY)
[](https://github.com/faiqueali017/The-Sparks-Foundation)
### # Task-5 : To Explore Sports Analytics (Level - Advanced)
_Please click on the images on right side to view my solution (preferably youtube)._
1. Perform ‘Exploratory Data Analysis’ on the provided dataset 'Indian Premier Leagure'
1. As a sports analyst, try to find out the most successful teams, players and factors contributing win or loss of a team.
1. Suggest teams or players a company should endorse for its products.
1. You can choose any of the tool of your choice (Python/R/Tableau/PowerBI/Excel)
1. Dataset link :[https://bit.ly/34SRn3b](https://bit.ly/34SRn3b)
1. Create storyboards. Screen record along with your audio explaining the charts and interpretations.
You can view all the tasks on my [youtube playlist](https://www.youtube.com/playlist?list=PLwWEREsMKfxZsqOsC5IJraTyVYYWz52UR) as well.
## Contact
Syed Faique Ali - [@faiqueali017](https://github.com/faiqueali017) - [email protected]
LinkedIn Profile: [https://www.linkedin.com/in/faique-ali/](https://www.linkedin.com/in/faique-ali/)
[contributors-shield]: https://img.shields.io/github/contributors/faiqueali017/REST_APIs-With-Flask-and-Python.svg?style=for-the-badge
[contributors-url]: https://github.com/faiqueali017/REST_APIs-With-Flask-and-Python/graphs/contributors
[forks-shield]: https://img.shields.io/github/forks/faiqueali017/REST_APIs-With-Flask-and-Python.svg?style=for-the-badge
[forks-url]: https://github.com/faiqueali017/REST_APIs-With-Flask-and-Python/network/members
[stars-shield]: https://img.shields.io/github/stars/faiqueali017/REST_APIs-With-Flask-and-Python.svg?style=for-the-badge
[stars-url]: https://github.com/faiqueali017/REST_APIs-With-Flask-and-Python/stargazers
[issues-shield]: https://img.shields.io/github/issues/faiqueali017/REST_APIs-With-Flask-and-Python.svg?style=for-the-badge
[issues-url]: https://github.com/faiqueali017/REST_APIs-With-Flask-and-Python/issues
[license-shield]: https://img.shields.io/github/license/othneildrew/Best-README-Template.svg?style=for-the-badge
[license-url]: https://github.com/othneildrew/Best-README-Template/blob/master/LICENSE.txt
[linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge&logo=linkedin&colorB=555
[linkedin-url]: https://www.linkedin.com/in/faique-ali/
[product-screenshot]: images/screenshot.png