GRIP - The Sparks Foundation

This repository contains the tasks that I completed while working as an Intern for The Sparks Foundation.

• Internship Category - Data Science & Business Analytics Task
• Internship Duration - 1 Month ( July-2021 )
• Internship Type - Work from Home

In this internship, we were provided a total of 8 Tasks and I was able to successfully complete all the 8 tasks within the given time-frame.

# Task-1 : Prediction using Supervised ML (Level - Beginner)

1. Predict the percentage of marks of an student based on the number of study hours.
2. This is a simple linear regression task as it involves just 2 variables.
3. Data can be found at http://bit.ly/w-data
4. You can use R, Python, SAS Enterprise Miner or any other tool.
5. What will be predicted score if a student studies for 9.25 hrs/ day?

# Task-2 : Prediction using Unsupervised ML (Level - Beginner)

1. From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.
2. Use R or Python or perform this task.
3. Data can be found at https://bit.ly/3cGyP8j

# Task-3 : Exploratory Data Analysis - Retail (Level - Beginner)

1. Perform ‘Exploratory Data Analysis’ on the provided dataset ‘SampleSuperstore’
2. As a business manager, try to find out the weak areas where you can work to make more profit.
3. What all business problems you can derive by exploring the data?
4. You can choose any of the tool of your choice (Python/R/Tableau/PowerBI/Excel)
5. Dataset link :https://bit.ly/3i4rbWl

# Task-4 : Exploratory Data Analysis - Terrorism (Level - Intermediate)

1. Perform ‘Exploratory Data Analysis’ on dataset ‘Global Terrorism’
2. As a security/defense analyst, try to find out the hot zone of terrorism.
3. What all security issues and insights you can derive by EDA?
4. You can choose any of the tool of your choice (Python/R/Tableau/PowerBI/Excel/SAP/SAS)
5. Dataset link : https://bit.ly/2TK5Xn5

# Task-5 : Exploratory Data Analysis - Sports (Level - Advanced)

1. Perform ‘Exploratory Data Analysis’ on dataset ‘Indian Premier League’
2. As a sports analysts, find out the most successful teams, players and factors contributing win or loss of a team.
3. Suggest teams or players a company should endorse for its products.
4. You can choose any of the tool of your choice (Python/R/Tableau/PowerBI/Excel/SAP/SAS)
5. Dataset link : https://bit.ly/34SRn3b