datascience

Welcome to the "AI_Course_Template" - the basic repository template for students enrolled in the Artificial Intelligence course in the Department of Computer Science for the academic years 2023/2024. This repository is designed to provide a standardized structure and set of guidelines for student projects, facilitating organized development, easy navigation, and consistent documentation.

Key Features:

Structured directory: Includes predefined folders for data (both raw and processed), source code, tests, and documentation, ensuring a clean and organized project workspace.

Comprehensive README Template: A guide to help students effectively document their project overview, goals, installation process, data descriptions, usage instructions, and contribution guidelines.

Resource Hub: Serves as a central location for essential resources, reference materials, and project-specific instructions.

Collaboration Ready: Configured to support collaborative projects, encouraging students to work together efficiently and share their progress.

Purpose:

This template is designed to streamline the project setup process, allowing students to focus more on the innovative aspects of AI and machine learning, rather than the initial setup and organization. By following this template, students will learn the importance of project organization, clear documentation, and consistent coding practices that are essential for any aspiring AI professional.

Trabajas como científico/a de datos para Data Insider, un reconocido equipo de asesores financieros con presencia global, y te ha sido solicitado que elabores un informe detallado para entender de manera objetiva el comportamiento de grandes corporaciones a nivel mundial a partir del año 2015.

R, Python and SQL tutorials for health data science

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