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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...
Read more
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...
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/qz4tv6/python
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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
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Python para Data Science with these
activities:
Review basic Python skills
Show steps
Refresh your memory or learn the fundamentals of Python to prepare for this course.
Browse courses on
Python Basics
Show steps
-
Review the syntax of Python variables, data types, and operators.
-
Write a simple Python program to print 'Hello, world!'
Follow Python tutorials for beginners
Show steps
Enhance your understanding by following guided tutorials that cover the basics of Python.
Show steps
-
Find tutorials that cover topics such as variables, data types, conditional statements, and loops.
-
Follow the tutorials step-by-step and practice writing Python code.
Solve Python coding exercises
Show steps
Reinforce your understanding by solving coding exercises that focus on Python fundamentals.
Show steps
-
Find online platforms or books that provide Python coding exercises.
-
Solve the exercises and review the solutions to identify your strengths and areas for improvement.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Python study group
Show steps
Engage with other learners and discuss Python concepts, projects, and challenges through a study group.
Show steps
-
Find or create a study group with other Python learners.
-
Meet regularly to discuss course material, ask questions, and share knowledge.
Attend a Python workshop or webinar
Show steps
Expand your Python skills by attending a workshop or webinar that focuses on specific topics.
Show steps
-
Find workshops or webinars that cover topics relevant to the course.
-
Register and attend the workshop or webinar.
Participate in a Python coding competition
Show steps
Challenge yourself and test your Python skills by participating in a coding competition.
Show steps
-
Find coding competitions that are relevant to Python and your skill level.
-
Prepare for the competition by practicing Python coding.
-
Participate in the competition and showcase your Python skills.
Create a knowledge base of course materials
Show steps
Organize and summarize course materials to improve retention and understanding.
Show steps
-
Review course notes, slides, assignments, and any other relevant materials.
-
Create a summary or outline of key concepts and ideas.
Review basic Python skills
Show steps
Refresh your memory or learn the fundamentals of Python to prepare for this course.
Browse courses on
Python Basics
Show steps
Show steps
Show steps
- Review the syntax of Python variables, data types, and operators.
- Write a simple Python program to print 'Hello, world!'
Follow Python tutorials for beginners
Show steps
Enhance your understanding by following guided tutorials that cover the basics of Python.
Show steps
Show steps
Show steps
- Find tutorials that cover topics such as variables, data types, conditional statements, and loops.
- Follow the tutorials step-by-step and practice writing Python code.
Solve Python coding exercises
Show steps
Reinforce your understanding by solving coding exercises that focus on Python fundamentals.
Show steps
Show steps
Show steps
- Find online platforms or books that provide Python coding exercises.
- Solve the exercises and review the solutions to identify your strengths and areas for improvement.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Python study group
Show steps
Engage with other learners and discuss Python concepts, projects, and challenges through a study group.
Show steps
Show steps
Show steps
- Find or create a study group with other Python learners.
- Meet regularly to discuss course material, ask questions, and share knowledge.
Attend a Python workshop or webinar
Show steps
Expand your Python skills by attending a workshop or webinar that focuses on specific topics.
Show steps
Show steps
Show steps
- Find workshops or webinars that cover topics relevant to the course.
- Register and attend the workshop or webinar.
Participate in a Python coding competition
Show steps
Challenge yourself and test your Python skills by participating in a coding competition.
Show steps
Show steps
Show steps
- Find coding competitions that are relevant to Python and your skill level.
- Prepare for the competition by practicing Python coding.
- Participate in the competition and showcase your Python skills.
Create a knowledge base of course materials
Show steps
Organize and summarize course materials to improve retention and understanding.
Show steps
Show steps
Show steps
- Review course notes, slides, assignments, and any other relevant materials.
- Create a summary or outline of key concepts and ideas.
Career center
Learners who complete Python para Data Science will develop knowledge and skills
that may be useful to these careers:
Project Manager
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 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 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 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 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
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 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 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 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 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 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 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
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 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 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.
For more career information including salaries, visit:
OpenCourser.com/course/qz4tv6/python
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.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/qz4tv6/python
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Leire Ahedo
Good to know
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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