Welcome to the RP Digital Tribe Data Science Internship! This 1-month program is designed to provide you with hands-on experience in data science, using tools and technologies to solve real-world problems. You will work on diverse data analysis tasks, gain experience in building predictive models, and learn to handle large datasets.

Internship Details

This internship includes multiple tasks with varying levels of complexity. You will complete at least 3 tasks to successfully finish the internship:

• Task 1: Titanic Survival Prediction – Build a model to predict whether a passenger survived the Titanic disaster.
• Task 2: Movie Rating Prediction – Predict movie ratings based on features such as genre, director, and actors.
• Task 3: Iris Flower Classification – Classify Iris flowers into species based on sepal and petal measurements.

How to Complete the Internship

To successfully complete this internship:

1. Work on any of the 3 tasks listed above and submit your results on GitHub.
2. Maintain a separate GitHub repository (named as RP Digital Tribe) for each task and share the link of the repository in the task submission form (which will be shared later via email).
3. Refer to online tutorials and resources like Google and YouTube for additional learning.
4. Record a video showcasing your work, explaining your approach, and demonstrating the final result. This will be shared on LinkedIn to build credibility and help you connect with peers.
5. Ensure to use the hashtag #RPDigitalTribe when sharing your videos on LinkedIn and include additional hashtags like #internship #datascience to increase visibility.

Completion and Certification

Upon completion of the internship, you will receive a Completion Certificate for your successful contribution and a Experience Letter to demonstrate your internship experience.

Examples of Internship Tasks

The following are the tasks you will complete during this internship:

1. Titanic Survival Prediction

Use the Titanic dataset to build a model that predicts whether a passenger survived or not. This classic project helps you understand classification models and data cleaning.

2. Movie Rating Prediction with Python

Build a model that predicts the rating of a movie based on features like genre, director, and actors. This project will teach you regression techniques and data preprocessing.

3. Iris Flower Classification

The Iris dataset is widely used for introductory classification tasks. Classify flowers based on sepal and petal measurements and learn about machine learning algorithms like KNN and decision trees.

4. Sales Prediction Using Python

In this task, you will work on predicting sales based on various features like advertising and customer behavior.

5. Credit Card Fraud Detection

Build a machine learning model to detect fraudulent transactions. This task will teach you about data imbalance, classification algorithms, and evaluation metrics.

Ready to Get Started?

Apply now and take the first step towards your career in Data Science with RP Digital Tribe. Gain valuable experience, enhance your skillset, and earn a certificate for completing the program.