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Arturo Javier Miguel de Priego Paz Soldán

En este curso basado en un proyecto, aprenderás a crear un programa en Python para resolver ecuaciones lineales, y explorarás objetos, sentencias y funciones de Python para procesar textos y números.

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En este curso basado en un proyecto, aprenderás a crear un programa en Python para resolver ecuaciones lineales, y explorarás objetos, sentencias y funciones de Python para procesar textos y números.

Al finalizar este proyecto habrás creado una aplicación que ayudará a los estudiantes y profesores a practicar con expresiones y ecuaciones lineales o de primer grado. Durante el proceso aprenderás a usar Jupyter para editar y ejecutar programas de Python; utilizar objetos con datos textuales y numéricos y en listas; controlar la secuencia de ejecución del programa; definir tus propias funciones y utilizar funciones de Python. En varios casos partiremos de algoritmos para crear programas y funciones. Esta experiencia servirá para comenzar a desarrollar programas para otras aplicaciones en matemática, ciencia, ingeniería y tecnología.

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What's inside

Syllabus

Introducción al proyecto Aprendiendo Python con textos, números y ecuaciones
En este curso basado en un proyecto, aprenderás a crear un programa en Python para resolver ecuaciones lineales, y explorarás objetos, sentencias y funciones de Python para procesar textos y números. Al finalizar este proyecto habrás creado una aplicación que ayudará a los estudiantes y profesores a practicar con expresiones y ecuaciones lineales o de primer grado. Durante el proceso aprenderás a usar Jupyter para editar y ejecutar programas de Python; utilizar objetos con datos textuales y numéricos y en listas; controlar la secuencia de ejecución del programa; definir tus propias funciones y utilizar funciones de Python. En varios casos partiremos de algoritmos para crear programas y funciones. Esta experiencia servirá para comenzar a desarrollar programas para otras aplicaciones en matemática, ciencia, ingeniería y tecnología.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Es apto para estudiantes y profesores que buscan una introducción a la programación en Python e interés en ecuaciones lineales o de primer grado
Este curso aborda un tema fundamental (ecuaciones lineales) desde un enfoque práctico
Explora conceptos esenciales de programación, como objetos, sentencias y funciones, lo que lo hace una base sólida para el desarrollo de programas en Python
La metodología basada en proyectos permite a los alumnos aplicar sus conocimientos de inmediato

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Reviews summary

Excellent introduction to python

This course provides an exceptional introduction to Python. The project-based approach allows learners to create a practical application and develop a solid understanding of Python's concepts. The course is well-paced and provides clear, concise explanations.
Covers core Python concepts in depth.
"Explorarás objetos, sentencias y funciones de Python para procesar textos y números."
Well-structured lessons with easy-to-follow explanations.
"Excelente para repasar conceptos básicos de programación y un proyecto aplicado a la educación."
Engaging and practical learning through project development.
"Al finalizar este proyecto habrás creado una aplicación que ayudará a los estudiantes y profesores a practicar con expresiones y ecuaciones lineales o de primer grado."
Additional resources beyond the course materials would be beneficial.
"lo que podría recomendar seria bueno que subiera el código completo como un recurso descargable"
Requires a significant time investment to complete the project.
"Muy buen proyecto. No es un proyecto para hacer en una ni dos horas. Entender y hasta mejorar las tareas me exigió en promedio una hora por tarea!! Ha que dedicarle tiempo, y vale la pena."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Aprendiendo Python con textos, números y ecuaciones with these activities:
Tutoriales de Introducción a Jupyter
Seguir tutoriales guiados para familiarizarse con Jupyter y mejorar las habilidades de programación.
Browse courses on Jupyter Notebook
Show steps
  • Completar tutoriales en línea sobre la interfaz y funcionalidad de Jupyter.
  • Experimentar con bloques de código y explorar funciones básicas.
Organizar y Revisar Materiales del Curso
Organizar, ampliar y revisar las notas, tareas, cuestionarios y exámenes del curso para mejorar la retención.
Show steps
  • Reunir y ordenar materiales del curso de varias fuentes.
  • Revisar y resumir notas de clase, diapositivas y lecturas.
  • Completar tareas y cuestionarios para reforzar la comprensión.
Show all two activities

Career center

Learners who complete Aprendiendo Python con textos, números y ecuaciones will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists often use Python to build machine learning models. This course can help you to build a foundation in Python programming, which is a valuable skill for Data Scientists. Additionally, the course covers topics such as data analysis and visualization, which are also important for Data Scientists.
Machine Learning Engineer
Machine Learning Engineers use Python to build and deploy machine learning models. This course can help you to build a foundation in Python programming, which is a valuable skill for Machine Learning Engineers. Additionally, the course covers topics such as data analysis and visualization, which are also important for Machine Learning Engineers.
Data Analyst
Data Analysts may use Python to analyze data and prepare reports for stakeholders. Being able to write Python programs with this course can help you to automate data collection, analysis, and reporting. This can free you to focus on more complex and strategic tasks, and potentially advance your career.
Software Engineer
Software Engineers often use Python to develop web applications, mobile applications, and other software products. This course can help you to build a foundation in Python programming, which is a valuable skill for Software Engineers. Additionally, the course covers topics such as data structures and algorithms, which are also important for Software Engineers.
Financial Analyst
Financial Analysts use Python to analyze financial data and make investment recommendations. This course can help you to build a foundation in Python programming, which is a valuable skill for Financial Analysts. Additionally, the course covers topics such as data analysis and visualization, which are also important for Financial Analysts.
Business Analyst
Business Analysts use Python to analyze data and make recommendations for improving business processes. This course can help you to build a foundation in Python programming, which is a valuable skill for Business Analysts. Additionally, the course covers topics such as data analysis and visualization, which are also important for Business Analysts.
Operations Research Analyst
Operations Research Analysts use Python to analyze data and make recommendations for improving operational efficiency. This course can help you to build a foundation in Python programming, which is a valuable skill for Operations Research Analysts. Additionally, the course covers topics such as data analysis and optimization, which are also important for Operations Research Analysts.
Data Engineer
Data Engineers use Python to build and maintain data pipelines. This course can help you to build a foundation in Python programming, which is a valuable skill for Data Engineers. Additionally, the course covers topics such as data structures and algorithms, which are also important for Data Engineers.
Quantitative Analyst
Quantitative Analysts use Python to analyze financial data and make investment decisions. This course can help you to build a foundation in Python programming, which is a valuable skill for Quantitative Analysts. Additionally, the course covers topics such as data analysis and visualization, which are also important for Quantitative Analysts.
Actuary
Actuaries use Python to analyze financial data and make risk assessments. This course can help you to build a foundation in Python programming, which is a valuable skill for Actuaries. Additionally, the course covers topics such as data analysis and visualization, which are also important for Actuaries.
Research Scientist
Research Scientists use Python to analyze data and conduct research. This course can help you to build a foundation in Python programming, which is a valuable skill for Research Scientists. Additionally, the course covers topics such as data analysis and visualization, which are also important for Research Scientists.
Computer Scientist
Computer Scientists use Python to develop new computer science theories and technologies. This course can help you to build a foundation in Python programming, which is a valuable skill for Computer Scientists. Additionally, the course covers topics such as data structures and algorithms, which are also important for Computer Scientists.
Statistician
Statisticians use Python to analyze data and draw conclusions. This course can help you to build a foundation in Python programming, which is a valuable skill for Statisticians. Additionally, the course covers topics such as data analysis and visualization, which are also important for Statisticians.
Mathematician
Mathematicians use Python to solve mathematical problems and develop new theories. This course can help you to build a foundation in Python programming, which is a valuable skill for Mathematicians. Additionally, the course covers topics such as data structures and algorithms, which are also important for Mathematicians.
Economist
Economists use Python to analyze data and make economic forecasts. This course can help you to build a foundation in Python programming, which is a valuable skill for Economists. Additionally, the course covers topics such as data analysis and visualization, which are also important for Economists.

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Aprendiendo Python con textos, números y ecuaciones.
Comprehensive introduction to programming in Python. It covers the basics of the language, as well as more advanced topics such as object-oriented programming and data structures. It good resource for beginners who want to learn Python in a structured and logical way.
Fast-paced introduction to Python. It covers the basics of the language, as well as more advanced topics such as object-oriented programming and data analysis. It good resource for beginners who want to learn Python quickly.
Practical guide to using Python for natural language processing. It covers the basics of natural language processing, as well as more advanced topics such as machine learning and deep learning. It good resource for data scientists and analysts who want to use Python for natural language processing.
Practical guide to using Python for deep learning. It covers the basics of deep learning, as well as more advanced topics such as convolutional neural networks and recurrent neural networks. It good resource for data scientists and analysts who want to use Python for deep learning.
Practical guide to programming in Python. It covers the basics of the language, as well as more advanced topics such as data structures and algorithms. It good resource for beginners who want to learn more about Python.
Is an advanced guide to programming in Python. It covers topics such as data structures, algorithms, and design patterns. It good resource for experienced Python programmers who want to improve their skills.
Practical guide to data analysis in Python. It covers the basics of data analysis, as well as more advanced topics such as machine learning and statistical modeling. It good resource for data scientists and analysts who want to use Python for data analysis.
Practical guide to using Pandas for data science. It covers the basics of Pandas, as well as more advanced topics such as data cleaning and data manipulation. It good resource for data scientists and analysts who want to use Pandas for data science.
Practical guide to using Scikit-Learn for data science. It covers the basics of Scikit-Learn, as well as more advanced topics such as machine learning and statistical modeling. It good resource for data scientists and analysts who want to use Scikit-Learn for data science.
Gentle introduction to programming in Python. It is written in a clear and concise style, and it good resource for beginners who have no prior programming experience.

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