This repository serves as the central hub for [Your Course Name]. This comprehensive course is designed to provide a well-rounded understanding of data science through two distinct learning paths: Business Case Study and Tech Stack.

Explore real-world applications of data science through three impactful use cases:

• Credit Scoring: Understand how data science can be employed to assess creditworthiness, enabling informed decision-making in financial contexts.

• Fraud Detection: Dive into the intricacies of fraud detection using data science techniques, safeguarding businesses against fraudulent activities.

• Customer Personalization: Explore the art of leveraging data to create personalized experiences for customers, enhancing satisfaction and engagement.

Develop a strong foundation in key technologies essential for data science practitioners:

• Python Basics: Acquire fundamental Python skills, laying the groundwork for data manipulation, analysis, and visualization.

• Python Analytics: Explore advanced Python functionalities for data analysis, enabling you to derive meaningful insights and draw informed conclusions.

• SQL Basics: Delve into the basics of Structured Query Language (SQL), essential for effective data management and retrieval.

Before diving into the course, ensure you have the following prerequisites:

• Basic understanding of programming concepts.
• Access to a Python environment (we recommend using Anaconda).
• A database system (SQLite, MySQL, or PostgreSQL) for SQL exercises.

├── Business_Case_Study/
│   ├── Credit_Scoring/
│   ├── Fraud_Detection/
│   └── Customer_Personalization/
├── Tech_Stack/
│   ├── Python_Basics/
│   ├── Python_Analytics/
│   └── SQL_Basics/
├── README.md
└── .gitignore

• Business_Case_Study: Contains materials related to the business case study learning path.
• Tech_Stack: Houses resources and exercises for the tech stack learning path.

1. Start by exploring the Business Case Study or Tech Stack folders based on your interest.

2. Each learning path folder contains dedicated sections for the specified use cases or topics.

3. Follow the provided instructions, review the code, and engage with the exercises to deepen your understanding.

4. Connect with the community: Feel free to ask questions, share insights, and collaborate with fellow learners through the repository's Issues section.

Thank you for choosing [Your Course Name]. We hope you find this learning experience insightful and empowering. Happy coding!

For any queries or concerns, please contact [Your Contact Information].