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Alex Aklson
«Лучше один раз увидеть, чем сто раз услышать». Всем нам знакомо это выражение. Оно справедливо и в случае, когда нужно объяснить выводы, полученные при анализе огромных наборов данных. Визуализация данных играет важную роль в представлении как мелких, так и крупных данных. Один из важнейших навыков аналитика данных — способность убедительно преподносить выводы, визуализируя данные и результаты в доступном и позитивном виде. Научитесь использовать программные инструменты для визуализации данных, и это поможет извлекать информацию, лучше понимать данные и принимать более разумные решения. Основная задача этого курса «Визуализация...
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«Лучше один раз увидеть, чем сто раз услышать». Всем нам знакомо это выражение. Оно справедливо и в случае, когда нужно объяснить выводы, полученные при анализе огромных наборов данных. Визуализация данных играет важную роль в представлении как мелких, так и крупных данных. Один из важнейших навыков аналитика данных — способность убедительно преподносить выводы, визуализируя данные и результаты в доступном и позитивном виде. Научитесь использовать программные инструменты для визуализации данных, и это поможет извлекать информацию, лучше понимать данные и принимать более разумные решения. Основная задача этого курса «Визуализация данных с помощью Python» — научить выбирать данные, которые на первый взгляд кажутся малозначимыми, и представлять их в том виде, в котором они будут иметь смысл. Для презентации данных существует множество методик, но в этом курсе мы будем использовать несколько библиотек визуализации на Python, в частности, Matplotlib, Seaborn и Folium. ОГРАНИЧЕННОЕ ПРЕДЛОЖЕНИЕ: приобретите подписку всего за 39 долл. США в месяц и получите доступ к упорядоченным по уровням материалам и сертификат по окончании курса.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Increases employability in the field of data analysis, in which professionals with data visualization skills are highly sought after
Helps learners create engaging and informative data visualizations that can be easily understood and shared
Builds a solid foundation in Python-based data visualization libraries, including Matplotlib, Seaborn, and Folium
Taught by experienced instructors in the field of data analysis and visualization
May require additional software or tools, which can incur costs for learners
Assumes a basic understanding of data analysis and Python programming

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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 Визуализация данных с помощью Python with these activities:
Review Data Science Fundamentals
Review essential Python skills that will be used in this course.
Browse courses on Python
Show steps
  • Revisit basic Python syntax (variables, data types, control flow).
  • Practice working with lists, tuples, and dictionaries.
  • Review basic statistical concepts such as mean, median, and standard deviation.
Explore Matplotlib Tutorials
Familiarize yourself with the features and capabilities of Matplotlib, a popular Python library for data visualization.
Browse courses on Matplotlib
Show steps
  • Follow an online tutorial on the basics of Matplotlib.
  • Create your own simple visualizations using Matplotlib.
  • Explore the Matplotlib documentation to learn about more advanced features.
Practice Matplotlib exercises
Sharpen plotting skills using Matplotlib, reinforcing knowledge of data visualization techniques.
Browse courses on Matplotlib
Show steps
  • Solve online Matplotlib exercises
  • Create custom visualizations from scratch
Six other activities
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Show all nine activities
Explore Seaborn tutorials
Expand knowledge of data visualization techniques by following guided tutorials focused on the Seaborn library.
Browse courses on Seaborn
Show steps
  • Find relevant Seaborn tutorials
  • Follow the tutorials and implement examples
Data Visualization Exercises
Reinforce your understanding of data visualization by practicing with real-world datasets.
Browse courses on Data Visualization
Show steps
  • Find a dataset online or create your own.
  • Visualize the data using Matplotlib.
  • Analyze the visualizations to identify trends and patterns.
Develop a Data Visualization Portfolio
Create a portfolio to showcase your data visualization skills and enhance your employability.
Browse courses on Data Visualization
Show steps
  • Gather a collection of your best data visualizations.
  • Create a website or online portfolio to display your work.
  • Share your portfolio with potential employers or clients.
Develop a data visualization portfolio
Showcase proficiency by compiling a portfolio of data visualizations that demonstrate various techniques learned in the course.
Browse courses on Data Presentation
Show steps
  • Select diverse datasets
  • Create visualizations using different Python libraries
  • Document the rationale and insights
Attend Data Science Meetups
Connect with other data science professionals and learn about industry trends and best practices.
Browse courses on Data Science
Show steps
  • Find local Data Science meetups using Meetup.com or other platforms.
  • Attend meetups regularly to network with other data scientists.
  • Participate in discussions and ask questions to learn from others.
Mentor Junior Data Scientists
Share your knowledge and expertise by mentoring junior data scientists.
Browse courses on Mentorship
Show steps
  • Identify a junior data scientist who would benefit from mentorship.
  • Set regular mentoring sessions to provide guidance and support.
  • Share your insights and experiences to help the mentee grow their skills and career.

Career center

Learners who complete Визуализация данных с помощью Python will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use their knowledge of math, statistics, and computer science to solve complex business problems. The course, _Visualizing Data with Python,_ may be useful in the role of a Data Scientist because it teaches the participant how to visualize data and communicate the results.
Business Analyst
Business Analysts use data to help businesses make better decisions. The course, _Visualizing Data with Python,_ may be useful in the role of a Business Analyst because it teaches the participant how to communicate data insights to stakeholders.
Operations Research Analyst
Operations Research Analysts use data to solve problems in a variety of fields, such as logistics, manufacturing, and healthcare. The course, _Visualizing Data with Python,_ may be useful in the role of an Operations Research Analyst because it teaches the participant how to visualize data and communicate the results.
Statistician
Statisticians use data to solve problems in a variety of fields, such as medicine, finance, and manufacturing. The course, _Visualizing Data with Python,_ may be useful in the role of a Statistician because it teaches the participant how to visualize data and communicate the results.
Data Analyst
A Data Analyst uses a variety of tools and techniques to clean, explore, and analyze data in order to identify trends, patterns, and insights. The course, _Visualizing Data with Python,_ may be useful in the role of a Data Analyst because it teaches the participant how to visualize data using multiple libraries, including Matplotlib, Seaborn, and Folium. These libraries help translate raw data into graphical representations for further analysis.   
Financial Analyst
Financial Analysts use data to make recommendations about investments and financial planning. The course, _Visualizing Data with Python,_ may be useful in the role of a Financial Analyst because it teaches the participant how to visualize data and communicate the results.
Quantitative Analyst
Quantitative Analysts use data to make investment decisions. The course, _Visualizing Data with Python,_ may be useful in the role of a Quantitative Analyst because it teaches the participant how to visualize data and communicate the results.
Actuary
Actuaries use data to assess risk and make decisions about insurance and other financial products. The course, _Visualizing Data with Python,_ may be useful in the role of an Actuary because it teaches the participant how to visualize data and communicate the results.
Market Researcher
Market Researchers collect and analyze data about consumers and markets. The course, _Visualizing Data with Python,_ may be useful in the role of a Market Researcher because it teaches the participant how to visualize data and communicate the results.
Artificial Intelligence Engineer
Artificial Intelligence Engineers design and develop artificial intelligence systems. The course, _Visualizing Data with Python,_ may be useful in the role of an Artificial Intelligence Engineer because it teaches the participant how to visualize data and communicate the results.
Data Engineer
Data Engineers are responsible for designing, building, and maintaining the infrastructure that stores and processes data. The course, _Visualizing Data with Python,_ may be useful in the role of a Data Engineer because it teaches the participant how to build visualizations using Python.
Data Architect
Data Architects design and manage the architecture of data systems. The course, _Visualizing Data with Python,_ may be useful in the role of a Data Architect because it teaches the participant how to visualize data and communicate the results.
Software Engineer
Software Engineers design, develop, and maintain software applications. The course, _Visualizing Data with Python,_ may be useful in the role of a Software Engineer because it teaches the participant how to visualize data and communicate the results.
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models. The course, _Visualizing Data with Python,_ may be useful in the role of a Machine Learning Engineer because it teaches the participant how to visualize data and communicate the results.
Database Administrator
Database Administrators design, build, and maintain databases. The course, _Visualizing Data with Python,_ may be useful in the role of a Database Administrator because it teaches the participant how to visualize data and communicate the results.

Reading list

We've selected 12 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 Визуализация данных с помощью Python.
Offering a practical guide to creating effective data visualizations, this book covers principles of visual perception, choosing appropriate chart types, and communicating insights clearly.
This academic textbook provides a comprehensive overview of visualization principles, data analysis techniques, and design considerations, offering a theoretical framework for understanding data visualization concepts.
Emphasizes the importance of ethical and accurate data visualization, exploring the role of storytelling and critical thinking in communicating data insights effectively.
Explores the intersection of data visualization and data analytics, covering techniques for visual data exploration, analysis, and storytelling, providing valuable insights into effective data communication.
Offers a comprehensive introduction to data analysis with Python, providing a foundation in data manipulation, cleaning, and visualization, which can enhance understanding of visualization techniques covered in the course.
This practical guide offers a non-technical approach to data visualization, covering essential concepts, principles, and common pitfalls, providing insights into effective visual communication.
This introductory textbook provides a clear and accessible overview of statistical concepts, offering a foundation for understanding the statistical principles behind data visualization.
While not directly focused on visualization, this book provides a solid foundation in statistical learning methods, which can complement the data visualization techniques covered in the course.
Introduces the popular ggplot2 package in R, providing a powerful tool for creating visually appealing and informative visualizations, which can complement the Python-based techniques covered in the course.
This beginner-friendly book provides a foundation in data analysis using Python, covering essential concepts and techniques, including data exploration, visualization, and statistical analysis.
This free online book provides a gentle introduction to statistics and probability, offering a foundation for understanding the underlying concepts behind data visualization.

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