Programación en Python II: aprendiendo a estructurar datos from Coursera

En este curso los estudiantes conocerán estructuras de datos secuenciales como listas, tuplas, stacks y colas. Luego, se presentarán estructuras no secuenciales como conjuntos y diccionarios, junto con sus ventajas y desventajas, lo que les permitirá escoger la representación apropiada para organizar datos de manera más eficiente. A continuación, se introducirán elementos de modelación para problemas más complejos mediante la programación orientada a objetos. Para finalizar se presentará la recursión como una estrategia alternativa a la resolución de problemas.

Al finalizar el curso, los estudiantes serán capaces de desarrollar sus propios programas informáticos, utilizando estructuras de datos y tipos propios, para implementar algoritmos más complejos y representar problemas interesantes a través de la programación.

What's inside

Syllabus

Introducción y bienvenida

En este curso estudiaremos los conceptos fundamentales para el desarrollo de algoritmos y su programación en computadores, enseñando conceptos que permitirán el desarrollo de programas utilizando diferentes estructuras de datos en Python 3. Podrás aprender a cómo definir estructuras de datos secuenciales y no secuenciales, así como tipos propios con orientación a objetos, y el paradigma de recursión. ¡Bienvenidos y bienvenidas !

Semana 1

En esta semana entenderemos el concepto y operaciones asociadas a tipos de datos secuenciales.

Semana 2

En esta semana seguiremos entendiendo el concepto y operaciones asociadas a otros tipos de datos secuenciales.

Semana 3

En esta semana entenderemos el concepto y operaciones asociadas a tipos de datos no-secuenciales.

Semana 4

En esta semana definiremos tipos de datos propios sencillos, usando conceptos de clases, objetos, atributos y métodos.

Semana 5

Esta semana entenderemos las herramientas de modelamiento para programas más complejos, como la interacción entre objetos y herencia.

Semana 6

En esta semana vamos a comprender el concepto de recursión y su uso para resolución de problemas.

Cierre

Muchas gracias por acompañarnos en este proceso de aprendizaje.En este curso enseñamos a definir y utilizar estructuras de datos secuenciales y no secuenciales, así como tipos propios con orientación a objetos, y el paradigma de recursión. Con las herramientas adquiridas podrás profundizar en otros tópicos, como el análisis de datos cada vez más complejos, y has dado el primer paso hacia la ciencia de datos.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Diseñado para principiantes que buscan comprender los conceptos básicos de las estructuras de datos

Cubre tipos de datos secuenciales y no secuenciales, así como conceptos de programación orientada a objetos

Introduce la recursión como un método para resolver problemas

Impartido por profesores con experiencia en el tema

Requiere un ordenador e Internet

Career center

Learners who complete Programación en Python II: aprendiendo a estructurar datos will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists utilize Python extensively in their work involving data analysis, modeling, and prediction. Programación en Python II provides a strong foundation in Python programming and data structures. By mastering these concepts, individuals will be well-equipped to develop and apply machine learning algorithms, enabling them to uncover valuable insights from data to solve complex business problems.

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Data Analyst

Data Analysts leverage their expertise in Python to collect, clean, and analyze data. The Programación en Python II course aligns perfectly with these needs, providing a comprehensive understanding of Python programming, data structures, and algorithmic problem-solving techniques. This course will aid Data Analysts in effectively handling and processing large datasets, extracting meaningful insights to drive informed decision-making.

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Applications Software Developer

An Applications Software Developer specializes in the development and deployment of computer applications that leverage Python. A course like Programación en Python II aligns with the foundational knowledge required to create applications for both existing and emerging technical environments. The strong emphasis on Python, coupled with the focus on data structures, could significantly aid in understanding and manipulating data within software applications.

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Machine Learning Engineer

Machine Learning Engineers develop and deploy machine learning models to solve real-world problems, with Python being a widely adopted language in this field. The Programación en Python II course provides a solid foundation in Python programming and data structures. This knowledge is essential for building, training, and evaluating machine learning models, enabling individuals to leverage data to make informed decisions and drive innovation.

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Data Engineer

Data Engineers build and maintain the infrastructure that supports data analysis and management. Knowledge of Python is crucial for this role, and Programación en Python II offers a solid foundation in Python programming, data structures, and algorithmic problem-solving techniques. This course enhances the skills needed to design, develop, and manage data pipelines that support data-driven organizations.

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Software Engineer

Software Engineers design, develop, and maintain software applications, with Python being a popular choice for web development, data analysis, and machine learning applications. The Programación en Python II course reinforces the Python programming skills crucial for Software Engineers. Additionally, the focus on data structures will aid in designing and developing efficient and scalable software applications.

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Business Intelligence Developer

A Business Intelligence Developer utilizes data to create solutions that improve business performance, and should have a strong understanding of Python. The course, Programación en Python II, provides a basis in Python programming and strengthens knowledge of data structures. With these skills, individuals will be able to more efficiently analyze and visualize complex data, enhancing their ability to make informed decisions.

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Full-Stack Developer

Full-Stack Developers are responsible for both the front-end and back-end development of web applications, with Python commonly used for back-end development. The Programación en Python II course strengthens the Python programming and data handling skills essential for back-end development. Familiarity with data structures is also crucial for managing and processing data efficiently within web applications.

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Statistician

Statisticians analyze and interpret data to provide insights and make predictions. Proficiency in Python is increasingly important for Statisticians, and the Programación en Python II course provides a solid foundation. By mastering Python programming and data structures, individuals will be well-equipped to collect, clean, and analyze data, enabling them to derive meaningful insights and make informed decisions.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze data and make investment decisions. Python is commonly utilized for data analysis and modeling in this role. The Programación en Python II course aligns with these requirements by providing a strong foundation in Python programming and data structures. Mastering these concepts is crucial for effectively managing and analyzing complex financial data, enabling individuals to make informed investment decisions.

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Web Developer

Web Developers leverage Python for back-end web development and data analysis. The Programación en Python II course strengthens the Python programming skills essential for Web Developers. Additionally, the focus on data structures will aid in designing and developing efficient and scalable web applications.

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Research Scientist

Research Scientists leverage Python for data analysis, modeling, and simulation in various scientific domains. The Programación en Python II course provides a strong foundation in Python programming, data structures, and algorithmic problem-solving techniques. This knowledge is essential for conducting research, analyzing data, and developing innovative solutions to complex scientific problems.

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Systems Analyst

Systems Analysts design and implement computer systems to meet business needs. A solid understanding of Python is beneficial in this role, and the Programación en Python II course provides a comprehensive foundation. Familiarity with data structures is also important for effectively managing and organizing data within complex systems.

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Data Architect

Data Architects design and manage data architectures for organizations. Proficiency in Python is becoming increasingly important in this role, and the Programación en Python II course offers a solid foundation. By mastering Python programming and data structures, individuals will be well-equipped to design, implement, and manage efficient and scalable data architectures that support data-driven decision-making.

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Artificial Intelligence Engineer

Artificial Intelligence Engineers develop and implement AI solutions to solve complex problems. Python is widely used in this field for machine learning, deep learning, and natural language processing. The Programación en Python II course reinforces the Python programming and data handling skills critical for Artificial Intelligence Engineers. Familiarity with data structures is also beneficial for managing and analyzing large datasets within AI applications.

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