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Joseph Santarcangelo
Научитесь применять Python для анализа данных. На этом курсе вы перейдете от основ Python к изучению различных типов данных. Вы узнаете, как подготовить данные к анализу, выполнить простой статистический анализ, визуализировать данные, cпрогнозировать тенденции на основе данных и многое другое! Рассматриваемые темы: 1) Импорт наборов данных 2) Очистка данных 3) Работа с кадрами данных 4) Обобщение данных 5) Построение регрессионных моделей машинного обучения 6) Создание конвейеров данных Курс «Анализ данных на Python» включает лекции, лабораторные работы и практические задания. Курс состоит из нескольких частей: Библиотеки для...
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Научитесь применять Python для анализа данных. На этом курсе вы перейдете от основ Python к изучению различных типов данных. Вы узнаете, как подготовить данные к анализу, выполнить простой статистический анализ, визуализировать данные, cпрогнозировать тенденции на основе данных и многое другое! Рассматриваемые темы: 1) Импорт наборов данных 2) Очистка данных 3) Работа с кадрами данных 4) Обобщение данных 5) Построение регрессионных моделей машинного обучения 6) Создание конвейеров данных Курс «Анализ данных на Python» включает лекции, лабораторные работы и практические задания. Курс состоит из нескольких частей: Библиотеки для анализа данных: вы научитесь использовать библиотеки Pandas, Numpy и Scipy на тестовом наборе данных. Вы познакомитесь с Pandas, библиотекой с открытым исходным кодом, и научитесь использовать ее для загрузки, обработки, анализа и визуализации интересных наборов данных. Затем мы рассмотрим еще одну библиотеку с открытым исходным кодом, scikit-learn, используем некоторые из входящих в нее алгоритмов машинного обучения для создания интеллектуальных моделей и построения интересных прогнозов. Пройдя этот курс и получив сертификат Coursera, вы также можете получить цифровой значок IBM. 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
Explores Python libraries for data analysis, building a foundation in industry-standard tools
Suitable for beginners seeking an introduction to data analysis using Python
Covers a range of foundational topics in data analysis, suitable for building a strong foundation
Teaches data analysis using Python, opening doors to careers and projects in data-driven fields
Includes hands-on labs and interactive materials, providing practical experience
Students may need to purchase a subscription for full access to course materials

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Reviews summary

Hands-on data analysis with python

The course is a great option for learning data analysis with Python. Students enjoyed the structured information and step-by-step approach. A few students found that the course material was outdated and superficial.
Informative slides
"Very good serve! The information is provided in stages and structured. A sufficient number of slides in the presentation!"
Materials may be outdated
"The guide for which is outdated and the course is not kept up to date"

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 Анализ данных с использованием Python with these activities:
Review Statistics
Brush up on probability to better understand how statistics are applied to problem-solving.
Show steps
  • Review basic probability concepts.
  • Practice solving probability problems.
  • Identify random events in data.
Join a Study Group for Data Analysis
Connect with other learners and exchange knowledge to reinforce your understanding.
Show steps
  • Find a study group or create your own.
  • Meet regularly to discuss course topics.
  • Work on projects or assignments together.
Develop a Data Analysis Pipeline
Create a data analysis pipeline to streamline and automate your analysis processes.
Browse courses on Data Pipelines
Show steps
  • Design the pipeline architecture.
  • Implement the pipeline using Python.
  • Test and validate the pipeline.
  • Deploy and monitor the pipeline.
One other activity
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Build a Predictive Model for a Real-World Problem
Apply your skills to solve a real-world problem.
Browse courses on Machine Learning Projects
Show steps
  • Identify a real-world problem that can be solved using machine learning.
  • Collect and prepare data for the problem.
  • Choose and train a machine learning model.
  • Evaluate the performance of the model.
  • Create a presentation or report on the project.

Career center

Learners who complete Анализ данных с использованием Python will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use data to help businesses make decisions. Data Analysts use techniques such as data mining, data cleansing, data analysis, and data visualization to analyze large data sets for patterns or trends. By using these techniques, Data Analysts find the story that the data has to tell and then share those insights with the business, often through reports or presentations. The course 'Анализ данных с использованием Python' will give you the skills needed to build a foundation in data analysis with Python. You will learn how to import data, clean it, and perform statistical analysis. This course will also teach you how to visualize data and build machine learning models.
Data Scientist
Data Scientists use complex modeling techniques that predict future outcomes. Data Scientists build systems that automatically detect patterns and insights in big data. Data Scientists combine programming skills with a deep understanding of mathematics and statistics to uncover actionable insights. The course 'Анализ данных с использованием Python' is a good starting point for people who want to become Data Scientists. This course will give you the foundation you need to understand the basics of data analysis and machine learning.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. Machine Learning Engineers use their knowledge of data, algorithms, and infrastructure to design, develop, and deploy machine learning solutions. The course 'Анализ данных с использованием Python' will give you a solid foundation in the basics of machine learning. You will learn how to build and train machine learning models using Python.
Data Engineer
Data Engineers design, build, and maintain the infrastructure that stores, processes, and analyzes data. Data Engineers use their knowledge of data, programming, and cloud computing to build scalable and reliable data pipelines. The course 'Анализ данных с использованием Python' will give you a good foundation in the basics of data engineering. You will learn how to use Python to load, process, and analyze data.
Business Analyst
Business Analysts use data to help businesses make better decisions. Business Analysts use techniques such as data mining, data analysis, and data visualization to analyze data for patterns or trends. Business Analysts use these insights to make recommendations to businesses on how to improve their operations or make better decisions. The course 'Анализ данных с использованием Python' will give you the skills you need to become a successful Business Analyst. You will learn how to import data, clean it, and perform statistical analysis. This course will also teach you how to visualize data and build machine learning models.
Data Visualization Specialist
Data Visualization Specialists use their knowledge of data visualization techniques and tools to create visual representations of data. Data Visualization Specialists use these visualizations to help businesses understand their data and make better decisions. The course 'Анализ данных с использованием Python' will give you the skills you need to become a successful Data Visualization Specialist. You will learn how to use Python to load, process, and analyze data. This course will also teach you how to use data visualization techniques and tools to create visual representations of data.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to solve complex business problems. Operations Research Analysts use these techniques to make recommendations on how to improve the efficiency and effectiveness of business operations. The course 'Анализ данных с использованием Python' will give you the skills you need to become a successful Operations Research Analyst. You will learn how to use Python to load, process, and analyze data. This course will also teach you how to use mathematical and statistical techniques to solve complex business problems.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical modeling to analyze financial data. Quantitative Analysts use these models to make recommendations on investments or trading strategies. The course 'Анализ данных с использованием Python' will give you the skills you need to become a successful Quantitative Analyst. You will learn how to use Python to load, process, and analyze financial data. This course will also teach you how to build machine learning models.
Statistician
Statisticians use mathematical and statistical techniques to collect, analyze, and interpret data. Statisticians use these techniques to make inferences about the world around us. The course 'Анализ данных с использованием Python' will give you the skills you need to become a successful Statistician. You will learn how to use Python to load, process, and analyze data. This course will also teach you how to use statistical techniques to make inferences about data.
Market Researcher
Market Researchers use data to understand the needs and wants of customers. Market Researchers use this information to help businesses develop new products and services that meet the needs of their customers. The course 'Анализ данных с использованием Python' will give you the skills you need to become a successful Market Researcher. You will learn how to use Python to load, process, and analyze data. This course will also teach you how to use market research techniques to understand the needs and wants of customers.
Data Architect
Data Architects design and build the data infrastructure that supports an organization's data analytics needs. Data Architects use their knowledge of data, architecture, and cloud computing to design and build scalable and reliable data pipelines. The course 'Анализ данных с использованием Python' will give you the skills you need to become a successful Data Architect. You will learn how to use Python to load, process, and analyze data. This course will also teach you how to design and build data pipelines.
Risk Analyst
Risk Analysts use data to identify and assess risks. Risk Analysts use this information to help businesses make decisions about how to mitigate risks. The course 'Анализ данных с использованием Python' will give you the skills you need to become a successful Risk Analyst. You will learn how to use Python to load, process, and analyze data. This course will also teach you how to identify and assess risks.
Software Engineer
Software Engineers design, develop, and maintain software applications. Software Engineers use their knowledge of programming languages and software development methodologies to build scalable and reliable software applications. The course 'Анализ данных с использованием Python' will give you a solid foundation in the basics of software development. You will learn how to use Python to build and deploy software applications.
Web Developer
Web Developers design, develop, and maintain websites. Web Developers use their knowledge of HTML, CSS, and JavaScript to build and deploy websites. The course 'Анализ данных с использованием Python' will give you a solid foundation in the basics of web development. You will learn how to use Python to build and deploy websites.

Reading list

We've selected ten 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 Анализ данных с использованием Python.
Comprehensive guide to using Python for machine learning. It covers everything from the basics of Python to more advanced topics such as supervised learning, unsupervised learning, and deep learning.
Comprehensive guide to using Python for natural language processing. It covers everything from the basics of natural language processing to more advanced topics such as machine translation, text classification, and sentiment analysis.
Comprehensive guide to using Python for data analysis. It covers everything from the basics of Python to more advanced topics such as data wrangling, machine learning, and data visualization.
Comprehensive guide to using R for data analysis. It covers everything from the basics of R to more advanced topics such as data wrangling, machine learning, and data visualization.
Great introduction to data science for beginners. It covers the basics of data science, including data wrangling, machine learning, and data visualization.
Great introduction to machine learning for beginners. It covers the basics of machine learning, including supervised learning, unsupervised learning, and deep learning.
Comprehensive guide to using Python for data visualization. It covers everything from the basics of data visualization to more advanced topics such as interactive visualization, geospatial visualization, and time series visualization.

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