University Microcredential in Data Analysis with Python + 3 Credits

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University Microcredential in Data Analysis with Python + 3 Credits

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$89,00
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135 hours

Duration

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  • Spanish

Language

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3 CR

Credits

Agenda

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Specialized teaching staff

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carlos alvarez gonzález

Technical Engineer in Computer Science and teacher in ICT skills, with extensive experience in technical support, implementation of ERP systems and technological training.

Professional experience:

More than 15 years of experience in the technological field as a consultant, analyst-programmer and ICT trainer. Specialized in implementation and support of ERP systems (SAGE), training in digital skills and maintenance of computer systems. Recent experience as a teacher in ICT skills in training projects of the Junta de Andalucía, accumulating more than 600 hours of face-to-face training.

Professional skills:

ERP systems and technical support (SAGE), Training in ICT skills, Computer programming, analysis and maintenance, Quality management (UNE-EN-ISO 9001).

Technical Engineer in Computer Science and teacher in ICT skills, with extensive experience in technical support, implementation of ERP systems and technological training.

Professional experience:

More than 15 years of experience in the technological field as a consultant, analyst-programmer and ICT trainer. Specialized in implementation and support of ERP systems (SAGE), training in digital skills and maintenance of computer systems. Recent experience as a teacher in ICT skills in training projects of the Junta de Andalucía, accumulating more than 600 hours of face-to-face training.

Professional skills:

ERP systems and technical support (SAGE), Training in ICT skills, Computer programming, analysis and maintenance, Quality management (UNE-EN-ISO 9001).

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Frequently asked questions

Description

In a world where data is the new oil, the ability to analyze it and extract valuable insights has become a crucial skill. The Data Analysis with Python Microcredential offers you the opportunity to acquire highly in-demand skills in today's job market. Python, with its versatility and powerful libraries such as NumPy, Pandas and Matplotlib, is the tool of choice for data analysis professionals. Throughout this course, you will learn from the fundamentals of the language to advanced techniques such as merging DataFrames and regressions. This course is ideal for those seeking to enhance their professional profile and gain a competitive advantage in sectors where data-based decision making is essential. The online modality allows you to learn at your own pace, ensuring you acquire the skills necessary to transform data into strategic decisions, propelling your career to new heights.

Job opportunities

- Data analyst in technology companies - Specialist in data visualization - Business intelligence technician - Data consultant - Developer of Python solutions for data analysis - Data scientist focused on regressions - Database manager - Professional in automation of analytical processes - Expert in optimization of predictive models

What does it prepare you for?

This course prepares you to use Python as a powerful tool in data analysis. You will learn from the installation and configuration of the development environment to the advanced use of libraries such as NumPy, Pandas and Matplotlib. You will be able to manage data types, variables, loops and conditionals, perform filtering, merging and apply regression techniques. Upon completion, you will be able to extract, analyze and visualize data efficiently, thus optimizing decision making in your professional field.

Who is it addressed to?

This course is designed for industry professionals and graduates looking to expand their skills in data analysis using Python. It is ideal for those interested in learning from environment installation, data types and flow control, to the use of libraries such as NumPy and Pandas, and advanced techniques such as linear and logistic regression.

Objectives

- Understand the installation and configuration of a development environment in Python. - Identify and use data types, variables and operators in Python. - Implement loops and conditionals to control the flow of the program. - Apply libraries such as NumPy, Pandas and Matplotlib in data analysis. - Perform efficient filtering and extraction of data for specific analysis. - Design and manage dynamic tables to summarize large data sets. - Run linear and logistic regressions to interpret relationships between variables.

University Microcredential in Data Analysis with Python + 3 Credits

$89,00