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Python para Data Science

Leire Ahedo
Este proyecto es un curso práctico y efectivo para aprender a programar en Python desde cero. Te permitirá adquirir los conocimientos de Python de manera práctica y aplicada. También te permitirá aprender las nociones básicas de un proyecto de Data Science y...
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Este proyecto es un curso práctico y efectivo para aprender a programar en Python desde cero. Te permitirá adquirir los conocimientos de Python de manera práctica y aplicada. También te permitirá aprender las nociones básicas de un proyecto de Data Science y generar tu primer modelo de inteligencia artificial en Python.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for learners with little to no prior experience in programming, making it ideal for beginners interested in learning Python
Provides foundational knowledge in Python, covering basic concepts and principles
Introduces learners to the fundamentals of Data Science, providing a broad overview of the field
Guides learners in building their first artificial intelligence model using Python, offering practical experience in AI techniques
Taught by industry experts with experience in programming and Data Science, ensuring up-to-date content and practical insights

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Reviews summary

Python for data science: practical and effective

Python para Data Science is a well-received course that teaches foundational Python programming and basic data science concepts. Students find it engaging and practical, and appreciate its clear explanations and hands-on exercises. Some wish for more in-depth coverage of data science topics and machine learning algorithms, and feel the pace of the course could be adjusted for beginners.
Suitable for beginners in Python and Data Science
"The best course ever!"
"Nice course. It helped me getting knowledge on Machine Learning."
Well-explained concepts and exercises
"perfecto!!"
"Debería tener más ejercicios de ML y de mayor nivel"
"Para aprender sobre como trabajar con datos similar a usar excel pero de manera mas automatizada esta perfecto"
Engaging and hands-on course
"He aprendido mucho"
"Entretenido, sirve como introducción y pequeña practica."
Occasionally encountered technical difficulties
"No explican como habilitar el entorno, es necesario para continuar con el curso e indispensable"
Some topics could be covered more thoroughly
"Un poco corto, deben tratar de dar mas profundidad en los temas."

Activities

Coming soon We're preparing activities for Python para Data Science. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Python para Data Science will develop knowledge and skills that may be useful to these careers:
Project Manager
Project Managers use Python to track the progress of projects and manage resources. This course may be helpful for aspiring Project Managers as it provides a foundation in Python and covers the basics of project management.
Data Scientist
Data Scientists use their knowledge of Python and other programming languages to analyze data, build models, and derive insights for businesses. This course may be helpful for aspiring Data Scientists as it provides a foundation in Python and introduces basic concepts of Data Science.
Machine Learning Engineer
Machine Learning Engineers use Python to develop and deploy machine learning models. This course may be useful for aspiring Machine Learning Engineers as it provides hands-on experience with Python and covers the basics of machine learning.
Business Analyst
Business Analysts use Python to analyze data and make recommendations to businesses. This course may be helpful for aspiring Business Analysts as it provides a foundation in Python and covers the basics of business analysis.
Operations Research Analyst
Operations Research Analysts use Python to analyze data and develop solutions to business problems. This course may be helpful for aspiring Operations Research Analysts as it provides a foundation in Python and covers the basics of operations research.
Statistician
Statisticians use Python to analyze data and draw conclusions. This course may be helpful for aspiring Statisticians as it provides a foundation in Python and covers the basics of statistics.
Software Engineer
Software Engineers use Python to develop software applications. This course may be useful for aspiring Software Engineers as it provides a foundation in Python and covers the basics of software development.
Data Analyst
Data Analysts use Python to clean, analyze, and visualize data. This course may be useful for aspiring Data Analysts as it provides a foundation in Python and covers the basics of data analysis.
Financial Analyst
Financial Analysts use Python to analyze financial data and make recommendations to businesses. This course may be helpful for aspiring Financial Analysts as it provides a foundation in Python and covers the basics of financial analysis.
Product Manager
Product Managers use Python to analyze data and make decisions about product development. This course may be helpful for aspiring Product Managers as it provides a foundation in Python and covers the basics of product management.
Data Engineer
Data Engineers use Python to build and maintain data pipelines. This course may be useful for aspiring Data Engineers as it provides a foundation in Python and covers the basics of data engineering.
Quantitative Analyst
Quantitative Analysts use Python to analyze data and develop trading strategies. This course may be helpful for aspiring Quantitative Analysts as it provides a foundation in Python and covers the basics of quantitative analysis.
Actuary
Actuaries use Python to analyze data and make recommendations on insurance and financial products. This course may be helpful for aspiring Actuaries as it provides a foundation in Python and covers the basics of actuarial science.
Research Scientist
Research Scientists use Python to analyze data and develop new technologies. This course may be helpful for aspiring Research Scientists as it provides a foundation in Python and covers the basics of research.
Data Journalist
Data Journalists use Python to analyze data and create visualizations that tell stories. This course may be helpful for aspiring Data Journalists as it provides a foundation in Python and covers the basics of data journalism.

Reading list

We've selected eight 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 Python para Data Science.
Covers the fundamentals of data science using Python, including data cleaning, exploration, and modeling. It valuable resource for those seeking a deeper understanding of data science concepts and techniques.
Provides a comprehensive introduction to Python programming, covering the fundamentals of programming as well as practical applications in data science. It is suitable for beginners and those with limited programming experience.
Covers the mathematical foundations of machine learning, providing a comprehensive overview of the field. It valuable resource for those seeking a deeper understanding of the mathematical and statistical principles underlying machine learning.
Provides a comprehensive guide to machine learning using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It is suitable for learners with some programming experience who want to apply machine learning algorithms in practice.
Provides a comprehensive guide to data science using Python, covering topics such as data cleaning, manipulation, visualization, and machine learning. It valuable resource for those seeking a practical and hands-on introduction to data science.
Reference guide for data analysis using Python, covering topics such as data cleaning, manipulation, and visualization. It is particularly useful for those who need a comprehensive resource on Python's data analysis capabilities.
Provides a hands-on introduction to deep learning using Python, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It is suitable for learners with some programming experience who want to explore the field of deep learning.
Focuses on practical applications of Python, teaching learners how to automate tasks, scrape websites, and analyze data. It is particularly helpful for those interested in exploring Python's capabilities beyond the classroom.

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