Data Science Tools and Technologies

Course Description

Welcome to our exciting course on Data Science Tools and Technologies! This intermediate-level course, offered by TecdeMonterreyX, is designed to equip you with the knowledge and skills necessary to navigate the complex world of data analysis tools. In today's data-driven business environment, understanding the right tools for data manipulation, management, and analysis is crucial for making informed decisions.

What students will learn

• Gain a comprehensive understanding of various commercial and open-source data analysis tools
• Learn about databases and their significance in data science projects
• Explore the benefits of cloud computing services in data science applications
• Develop skills to differentiate between tools for programmers and business users
• Understand the role of data scientists and citizen data scientists in the field

Pre-requisites

• Knowledge of programming languages (preferably R or Python)
• Familiarity with data manipulation languages (SQL)
• Basic understanding of data analysis concepts

Course Content

• Introduction to data science tools and their classifications
• Comparison of various data analysis tools and their applications
• Databases and their importance in data science projects
• Cloud computing services and their benefits for data science
• Role of data scientists and citizen data scientists
• Tools for programmers vs. tools for business users
• Automated data analysis techniques
• Best practices for data-driven decision making

Who this course is for

• Aspiring data scientists and analysts
• Business professionals looking to enhance their data analysis skills
• IT professionals interested in expanding their knowledge of data science tools
• Students pursuing careers in data-driven fields
• Anyone interested in understanding the landscape of data science technologies

Real-world Applications

• Select appropriate tools for various data analysis tasks
• Implement data-driven decision-making processes in their organizations
• Collaborate effectively with data scientists and IT professionals
• Leverage cloud computing services for data science projects
• Automate data analysis processes for improved efficiency
• Bridge the gap between technical and business aspects of data science

Syllabus

1. Introduction to Data Science
2. Databases in Data Science
3. Data Science Tools and Technologies
4. Cloud Computing for Data Science