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Rav Ahuja
and
Alex Aklson
Люди с древних времен занимаются поиском закономерностей и тенденций в данных. Древние египтяне использовали данные переписи для более эффективного сбора налогов, а также из года в год точно предсказывали разлив Нила. С тех времен люди, занимающиеся анализом данных, сделали эту сферу деятельности отдельной уникальной наукой. И эта наука называется «обработка и анализ данных». В этом курсе мы познакомимся с несколькими специалистами по обработке и анализу данных и разберемся, что представляет собой эта наука в современном мире.
Register for this course and see more details by visiting:
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Know what's good ,
what to watch for , and
possible dealbreakers
Introduces learners to the history and applications of data processing and analysis
Explores industry-standard methods in data collection, storage, and retrieval
Examines a variety of data analysis techniques, including statistical modeling, machine learning, and data visualization
Taught by Alex Aklson and Rav Ahuja, who have extensive experience in data analysis and management
Builds a strong foundation for learners interested in pursuing careers in data science, data analytics, and related fields
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Read 'Data Science for Business'
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Read 'Data Science for Business' to get an overview of the field of data science and how it can be used in business.
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Data Science for Business: What You Need to...
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Read through the book, taking notes on the key concepts.
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Complete the exercises at the end of each chapter.
Follow online tutorials on data science
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Follow online tutorials on data science to supplement your learning in the course.
Browse courses on
Data Science
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Find online tutorials on data science that are relevant to the topics you're learning in the course.
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Follow the tutorials and complete the exercises.
Review the basics of data analysis
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Review the basics of data analysis to ensure you have a strong foundation for the course.
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Data Analysis
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Read through your old notes or textbooks on data analysis.
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Complete some practice problems or exercises on data analysis.
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Join a data science study group
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Join a data science study group to connect with other learners and collaborate on projects.
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Find a data science study group online or in your local area.
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Attend the study group meetings regularly.
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Participate in discussions and collaborate on projects.
Solve data analysis problems
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Solve data analysis problems to practice applying the concepts you're learning in the course.
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Data Analysis
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Find a dataset online or in a textbook.
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Formulate a question that you want to answer using the data.
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Analyze the data using the techniques you've learned in the course.
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Write up your findings in a report.
Attend a data science workshop
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Attend a data science workshop to learn new skills and network with other data scientists.
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Find a data science workshop that is relevant to your interests.
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Register for the workshop and attend the sessions.
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Participate in the discussions and activities.
Create a data visualization
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Create a data visualization to help you understand and communicate the results of your data analysis.
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Data Visualization
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Choose a dataset that you're interested in.
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Explore the data and identify the key insights.
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Choose a data visualization that will effectively communicate your insights.
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Create the data visualization using a tool like Tableau or Google Data Studio.
Start a data science project
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Start a data science project to apply the concepts you're learning in the course and build your portfolio.
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Identify a problem that you want to solve using data science.
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Gather the data that you need to solve the problem.
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Analyze the data and develop a solution to the problem.
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Deploy your solution and track its results.
Read 'Data Science for Business'
Show steps
Read 'Data Science for Business' to get an overview of the field of data science and how it can be used in business.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
Show steps
Show steps
- Read through the book, taking notes on the key concepts.
- Complete the exercises at the end of each chapter.
Follow online tutorials on data science
Show steps
Follow online tutorials on data science to supplement your learning in the course.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Find online tutorials on data science that are relevant to the topics you're learning in the course.
- Follow the tutorials and complete the exercises.
Review the basics of data analysis
Show steps
Review the basics of data analysis to ensure you have a strong foundation for the course.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Read through your old notes or textbooks on data analysis.
- Complete some practice problems or exercises on data analysis.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a data science study group
Show steps
Join a data science study group to connect with other learners and collaborate on projects.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Find a data science study group online or in your local area.
- Attend the study group meetings regularly.
- Participate in discussions and collaborate on projects.
Solve data analysis problems
Show steps
Solve data analysis problems to practice applying the concepts you're learning in the course.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Find a dataset online or in a textbook.
- Formulate a question that you want to answer using the data.
- Analyze the data using the techniques you've learned in the course.
- Write up your findings in a report.
Attend a data science workshop
Show steps
Attend a data science workshop to learn new skills and network with other data scientists.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Find a data science workshop that is relevant to your interests.
- Register for the workshop and attend the sessions.
- Participate in the discussions and activities.
Create a data visualization
Show steps
Create a data visualization to help you understand and communicate the results of your data analysis.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset that you're interested in.
- Explore the data and identify the key insights.
- Choose a data visualization that will effectively communicate your insights.
- Create the data visualization using a tool like Tableau or Google Data Studio.
Start a data science project
Show steps
Start a data science project to apply the concepts you're learning in the course and build your portfolio.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Identify a problem that you want to solve using data science.
- Gather the data that you need to solve the problem.
- Analyze the data and develop a solution to the problem.
- Deploy your solution and track its results.
Career center
Learners who complete Что такое обработка и анализ данных? will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst examines and interprets large amounts of data using various techniques to uncover patterns, trends, and anomalies. This course from IBM Skills Network provides an introduction to the skills and knowledge required for a successful career as a Data Analyst. Learners will gain insights into data processing, analysis, and visualization techniques, which form the foundation of data analytics. By understanding the principles and practices covered in this course, individuals can enhance their ability to derive meaningful insights from data and contribute to data-driven decision-making.
Data Scientist
Data Scientist
A Data Scientist possesses advanced skills in data analysis, machine learning, and statistical modeling. This course offered by IBM Skills Network aligns well with the foundational knowledge required for a Data Scientist. Learners will gain an understanding of data processing, visualization, and analysis techniques, providing a strong basis for further exploration in data science. Additionally, the course provides insights into the practical applications of data science, making it valuable for aspiring Data Scientists looking to build a solid foundation in the field.
Business Analyst
Business Analyst
A Business Analyst bridges the gap between technology and business by analyzing data to understand business needs and translating them into technical solutions. This IBM Skills Network course provides a solid foundation for individuals seeking a career as a Business Analyst. Learners will acquire skills in data analysis, visualization, and interpretation, enabling them to effectively identify and solve business problems using data-driven insights.
Market Research Analyst
Market Research Analyst
A Market Research Analyst collects, interprets, and analyzes market data to understand consumer behavior and trends. The course offered by IBM Skills Network provides a valuable introduction to data analysis and interpretation techniques, which are essential for success in market research. Learners will gain insights into data collection, analysis, and reporting, enabling them to effectively contribute to market research initiatives.
Financial Analyst
Financial Analyst
A Financial Analyst examines financial data to assess the performance and risks of companies or investments. This course from IBM Skills Network provides a foundation in data analysis and interpretation, which are crucial skills for Financial Analysts. Learners will gain an understanding of data processing, visualization, and statistical analysis techniques, enabling them to effectively analyze financial data and make informed decisions.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical techniques to improve business operations and decision-making. This IBM Skills Network course provides a strong foundation in data analysis and modeling, which are essential skills for Operations Research Analysts. Learners will gain insights into data collection, analysis, and optimization techniques, enabling them to effectively contribute to data-driven decision-making in various industries.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains data infrastructure and systems. This course offered by IBM Skills Network provides an introduction to data management and processing techniques, which are fundamental skills for Data Engineers. Learners will gain insights into data storage, retrieval, and analysis, enabling them to effectively design and manage data systems that support data-driven initiatives.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course from IBM Skills Network may provide a useful foundation for Software Engineers who wish to specialize in data-driven applications. Learners will gain insights into data analysis and visualization techniques, enabling them to effectively incorporate data into software solutions.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases to ensure data integrity and availability. This IBM Skills Network course provides an introduction to data management and processing techniques, which are valuable skills for Database Administrators. Learners will gain insights into data storage, retrieval, and analysis, enabling them to effectively administer and maintain databases for various applications.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data and make investment decisions. This course from IBM Skills Network may provide a helpful foundation for Quantitative Analysts who wish to enhance their data analysis and modeling skills. Learners will gain insights into data analysis, statistical modeling, and visualization techniques, enabling them to effectively contribute to investment analysis and decision-making.
Actuary
Actuary
An Actuary assesses and manages financial risks using mathematical and statistical techniques. This IBM Skills Network course may provide a useful foundation for Actuaries who wish to enhance their data analysis and modeling skills. Learners will gain insights into data analysis, statistical modeling, and visualization techniques, enabling them to effectively contribute to risk assessment and management in various industries.
Epidemiologist
Epidemiologist
An Epidemiologist investigates the causes and distribution of diseases in populations. This course from IBM Skills Network may provide a useful foundation for Epidemiologists who wish to enhance their data analysis and modeling skills. Learners will gain insights into data analysis, statistical modeling, and visualization techniques, enabling them to effectively analyze health data and contribute to disease prevention and control.
Statistician
Statistician
A Statistician designs, conducts, and interprets statistical studies to extract meaningful insights from data. This course from IBM Skills Network may provide a helpful foundation for Statisticians who wish to enhance their data analysis and modeling skills. Learners will gain insights into data analysis, statistical modeling, and visualization techniques, enabling them to effectively design and conduct statistical studies.
Data Journalist
Data Journalist
A Data Journalist uses data to tell stories and inform the public. This course from IBM Skills Network may provide a useful foundation for Data Journalists who wish to enhance their data analysis and visualization skills. Learners will gain insights into data analysis, data visualization, and storytelling techniques, enabling them to effectively communicate data-driven insights to a wide audience.
Risk Analyst
Risk Analyst
A Risk Analyst identifies, assesses, and manages risks to an organization. This course from IBM Skills Network may provide a useful foundation for Risk Analysts who wish to enhance their data analysis and modeling skills. Learners will gain insights into data analysis, risk assessment, and visualization techniques, enabling them to effectively contribute to risk management initiatives in various industries.
For more career information including salaries, visit:
OpenCourser.com/course/onensx/chto
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
Что такое обработка и анализ данных?.
Provides a comprehensive overview of advanced analytics with Spark. It great resource for students and professionals who want to learn about the different Spark libraries and how to use them to solve real-world problems.
Provides a practical guide to machine learning using Scikit-Learn, Keras, and TensorFlow. It great resource for students and professionals who want to learn how to use these tools to solve real-world problems.
Provides a practical guide to deep learning using Python. It great resource for students and professionals who want to learn how to use deep learning to solve real-world problems.
Provides a comprehensive overview of data science, including data collection, analysis, and visualization. It great resource for business professionals who want to learn more about data science and how it can be used to improve their decision-making.
Save
Provides a comprehensive overview of deep learning. It great resource for students and professionals who want to learn about the different types of deep learning algorithms and how to use them to solve real-world problems.
Provides a comprehensive overview of data science. It great resource for students and professionals who want to learn about the different aspects of data science, including data collection, analysis, and visualization.
Save
Provides a comprehensive overview of data mining. It great resource for students and professionals who want to learn about the different data mining algorithms and how to use them to solve real-world problems.
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Provides a step-by-step guide to data analysis using the R programming language. It great resource for students and professionals who want to learn how to use R to analyze data.
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Provides a practical guide to storytelling with data. It great resource for students and professionals who want to learn how to communicate data insights effectively.
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Provides a practical introduction to data visualization. It great resource for students and professionals who want to learn how to create effective data visualizations.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/onensx/chto
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Time
2 hours
Via
Coursera
Institutions
IBM
IBM Skills Network
Instructors
Rav Ahuja
Alex Aklson
Good to know
Introduces learners to the history and applications of data processing and analysis
Explores industry-standard methods in data collection, storage, and retrieval
Examines a variety of data analysis techniques, including statistical modeling, machine learning, and data visualization
Taught by Alex Aklson and Rav Ahuja, who have extensive experience in data analysis and management
Builds a strong foundation for learners interested in pursuing careers in data science, data analytics, and related fields
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