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Explorando funciones lineales con Python

Arturo Javier Miguel de Priego Paz Soldán
En este proyecto guiado programarás interfaces para explorar funciones lineales de la forma ?(?)=??+? . El proyecto está dirigido especialmente a los docentes de la escuela secundaria con conocimientos básicos de programación de computadoras. Los programas...
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En este proyecto guiado programarás interfaces para explorar funciones lineales de la forma ?(?)=??+? . El proyecto está dirigido especialmente a los docentes de la escuela secundaria con conocimientos básicos de programación de computadoras. Los programas han sido diseñados teniendo en cuenta aspectos pedagógicos de la matemática y están documentados para que puedas mejorarlos y adaptarlos a tus clases con otras herramientas de la Internet.   Durante el proyecto, utilizarás el lenguaje Python 3.8 en Jupyter Notebook con interfaces de ipywidgets para procesar números y cadenas de caracteres y realizarás tareas de análisis y de programación mediante guías en vídeos y en un cuaderno de prácticas que incluye enlaces a recursos informáticos y matemáticos. Los vídeos duran aproximadamente una hora y las tareas requieren dedicar alrededor de dos horas. Al finalizar el proyecto estarás en capacidad de programar interfaces básicas para ayudar a los estudiantes a descubrir patrones aritméticos y algebraicos en las funciones lineales.   Nota: los proyectos guiados de la serie "Explorando ... con Python" contienen varias tareas similares para que puedan ser elegidos independientemente. Si tomas funciones cuadráticas no será necesario llevar funciones lineales; ni funciones trigonométricas si eliges funciones trigonométricas inversas.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a basics-first foundation to help learners gain confidence
Helps learners understand linear functions and algebraic relationships
Suitable for secondary school teachers and mathematics instructors
Utilizes Python 3.8 in Jupyter Notebook for hands-on learning
Emphasizes pedagogical aspects of mathematics, addressing subject in a clear and structured way

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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 Explorando funciones lineales con Python with these activities:
Review prerequisite material on calculus
Ensure a solid foundation in calculus as it is essential for understanding linear algebra.
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  • Review lecture notes, textbooks, or online resources on calculus.
  • Solve practice problems covering various aspects of calculus.
  • Participate in online forums or discussion groups to clarify any doubts.
Review core concepts of linear algebra
Brush up on the fundamental principles of linear algebra to ensure a solid foundation for this course on matrices.
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  • Review lecture notes and textbooks on linear algebra.
  • Solve practice problems covering various aspects of linear algebra.
  • Participate in online forums or discussion groups to clarify any doubts.
Explore interactive Python tutorials for linear algebra
Familiarize yourself with Python libraries and tools commonly used in linear algebra, enhancing your ability to apply these concepts in practice.
Browse courses on Jupyter Notebook
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  • Identify online tutorials or courses that provide interactive Python exercises for linear algebra.
  • Follow the tutorials step-by-step, experimenting with different examples.
  • Implement the learned concepts in your own Python scripts.
Two other activities
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Complete practice problems on matrix operations
Reinforce your understanding of matrix operations through repetitive practice, improving your accuracy and speed in solving linear algebra problems.
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  • Find online problem sets or textbooks that provide practice problems on matrix operations.
  • Solve a significant number of problems, covering various types of matrix operations.
  • Identify patterns and develop strategies for solving different types of matrix problems efficiently.
Develop a visual representation of linear algebra concepts
Create a visual representation, such as a diagram, infographic, or animation, to deepen your understanding of linear algebra concepts and their relationships.
Show steps
  • Identify a specific linear algebra concept you want to visualize.
  • Brainstorm and sketch out different ways to represent the concept visually.
  • Use appropriate software or tools to create the visual representation.
  • Share your visual representation with others for feedback and discussion.

Career center

Learners who complete Explorando funciones lineales con Python will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use their expertise in data mining and machine learning to find patterns and generate insights from large datasets. By taking this online course, you can enhance your data analysis skills using Python 3.8.
Software Developer
In this project, you will use Jupyter Notebook with ipywidgets interfaces to process numbers and strings, which will help build a foundation for your future endeavors in Software Development, particularly for Machine Learning.
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. This course may be useful for developing the Python programming and data analysis skills commonly used in this role.
Business Analyst
Business Analysts use data and analysis to identify opportunities and solve problems for businesses. This course may be useful for developing the Python programming and data analysis skills commonly used in this role.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to improve the efficiency and effectiveness of organizations. This course may be useful for developing the Python programming and data analysis skills commonly used in this role.
Statistician
Statisticians collect, analyze, and interpret data to provide insights and make predictions. This course may be useful for developing the Python programming and data analysis skills commonly used in this role.
Financial Analyst
Financial Analysts help organizations make informed decisions by providing insights and recommendations on financial matters. This course may be useful for developing the Python programming and data analysis skills commonly used in this role.
Data Scientist
Data Scientists use their expertise in data mining, statistics, and machine learning to extract insights and make predictions from data. This course may be useful for developing the Python programming and data analysis skills commonly used in this role.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course may be useful for developing the Python programming and data analysis skills commonly used in this role.
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. This course may be useful for developing the Python programming and data analysis skills commonly used in this role.
Market Research Analyst
Market Research Analysts conduct research to gather information about consumer preferences and market trends. This course may be useful for developing the data analysis and visualization skills commonly used in this role.
Data Engineer
Data Engineers build and maintain the infrastructure that stores and processes data. This course may be useful for developing the Python programming and data analysis skills commonly used in this role.
Operations Manager
Operations Managers plan and oversee the day-to-day operations of an organization. This course may be useful for developing the data analysis and visualization skills commonly used in this role.
Consultant
Consultants provide advice and guidance to organizations on a variety of topics. This course may be useful for developing the data analysis and visualization skills commonly used in this role.
Project Manager
Project Managers plan and execute projects to achieve specific goals. This course may be useful for developing the data analysis and visualization skills commonly used in this role.

Reading list

We've selected 14 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 Explorando funciones lineales con Python.
Provides a comprehensive introduction to computer vision with Python. It valuable resource for students who want to develop a strong foundation in computer vision with Python.
Provides a comprehensive introduction to deep learning with Python. It valuable resource for students who want to develop a strong foundation in deep learning with Python.
Provides a comprehensive introduction to natural language processing with Python. It valuable resource for students who want to develop a strong foundation in natural language processing with Python.
Provides a comprehensive overview of the mathematical tools and techniques used in economic analysis, including linear functions. It valuable resource for students who want to develop a strong foundation in mathematics for economics.
Provides a comprehensive introduction to the mathematical tools and techniques used in machine learning, including linear functions. It valuable resource for students who want to develop a strong foundation in mathematics for machine learning.
Provides a comprehensive introduction to deep learning, which subfield of machine learning that uses linear functions. It valuable resource for students who want to develop a strong foundation in deep learning.
Provides a comprehensive introduction to statistics for machine learning. It valuable resource for students who want to develop a strong foundation in statistics for machine learning.
Provides a comprehensive introduction to machine learning with Python. It valuable resource for students who want to develop a strong foundation in machine learning with Python.
Provides a comprehensive introduction to Python for data analysis. It valuable resource for students who want to develop a strong foundation in Python for data analysis.
Provides a comprehensive introduction to data science from scratch. It valuable resource for students who want to develop a strong foundation in data science.
Provides a clear and concise introduction to the mathematical tools and techniques used in economics and business, including linear functions. It good choice for students who are looking for a more accessible introduction to the subject.
Provides a comprehensive introduction to probability, which is the mathematical foundation for statistics. It valuable resource for students who want to develop a strong foundation in mathematics for statistics.
Provides a comprehensive introduction to linear algebra, which is the mathematical foundation for linear functions. It valuable resource for students who want to develop a deeper understanding of the subject.

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