Data Science Skill Assessment

Background

In this assessment, you are provided with a dataset containing information about Life Expectancy and Socio-Economic data from the World Bank. Your task is to analyze this dataset to uncover insightful patterns and trends. This is an open-ended task designed to allow you to showcase your creativity, analytical skills, and ability to derive meaningful information from data. You have the liberty to choose the analyses to perform, insights to uncover, and the kind of visualizations to use.

Task

Consider this dataset as a playground where you can unleash your data science prowess. You are free to navigate through the data in any way you see fit. Here are some guidelines to steer your journey:

1. Dataset Inspection: Begin by conducting a preliminary inspection of the dataset. Familiarize yourself with the different variables available, handle missing values if any, and perform necessary data cleaning and transformation tasks. Document any patterns or inconsistencies you observe during this phase.

2. Exploratory Data Analysis (EDA): Carry out an exploratory data analysis to identify patterns, relationships, or anomalies in the data. This could include the investigation of correlations between variables, distribution analysis of certain features, etc.

3. Data Visualization: Create visualizations to help convey the insights you uncover during your analysis. Visualizations can be in the form of graphs, charts, or any other appropriate formats. Make sure your visualizations are clear and well-labeled.

Final Output

Your final submission should be a report intertwined with the code used for the analysis. This document can be in the form of a Jupyter Notebook, R Markdown document, or any other similar formats which allows for a seamless integration of code and narrative. The report should encapsulate:

• A brief introduction to the dataset
• Methods and techniques used during the analysis
• Key findings and insights derived from the analysis
• Visualizations along with explanations
• Conclusion with possible recommendations or points for further investigation

Mandatory Code & Documentation: Ensure to encapsulate your journey in well-structured and documented code. Showcase your proficiency in crafting clean, efficient, and reusable code. Your scripts should clearly narrate the steps and methodologies adopted during your exploration.

Evaluation Criteria

Your submission will be evaluated based on the following criteria:

1. Understanding of Data: Demonstrated understanding of the data and its nuances.
2. Analytical Skills: The ability to identify complex patterns and trends in the data.
3. Visualization Skills: The ability to create meaningful and insightful visualizations.
4. Reporting Skills: Clear articulation of findings, with a logical flow of the report.
5. Code Quality: Clean, well-organized, and documented code.

Submission

To submit your project, we offer you two avenues: either create a new GitHub repository or fork the original repository that we have provided. If you do not already have a GitHub account, you will need to create one to submit your project. Creating an account is straightforward and can be done here. Below are the detailed instructions to guide you through both processes:

Option 1: Create a New Repository

1. New Repository: Create a new GitHub repository to host your project. If you are unfamiliar with this process, here is a guide on how to create a new repository.

2. Clone the Repository: Once created, clone the repository to your local system to begin working on the project.

3. Copy the Necessary Files: Copy the necessary files from the original repository into your newly created repository to ensure you have all the required data and documents to begin your analysis.

Option 2: Fork the Original Repository

1. Fork the Repository: You can also choose to fork the original repository that we have provided. This creates a personal copy of the repository in your GitHub account. Follow this guide on how to fork a repository if you're new to forking.

2. Clone Your Forked Repository: Post forking, clone it to your local system to initiate your work on the project.

Common Steps

1. Develop Your Project: Begin your project, integrating both your code and narrative into a document, in alignment with the "Final Output" section outlined above.

2. Commit and Push: Regularly commit and push your changes to your GitHub repository, ensuring to provide descriptive commit messages that effectively narrate the changes at each step.

3. Individual Contribution: Your submission should reflect your individual efforts and insights. Collaboration with other candidates is not permitted. We urge you to work independently, showcasing your personal skill set and insights.

4. Share Your Repository: Once your project is ready, share the link to your repository with us. Make sure the repository is public so that the evaluation panel can access and review your work seamlessly.

Best of luck!