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Dhiraj Kumar

Learn effective data collection techniques. This course will teach you data collection techniques from a data scientist's perspective. It will also teach you how to apply those data collection techniques effectively.

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Learn effective data collection techniques. This course will teach you data collection techniques from a data scientist's perspective. It will also teach you how to apply those data collection techniques effectively.

Understanding various data collection techniques and how to apply them effectively is essential. In this course, Data Collection for Data Scientists, you’ll gain the ability to collect data effectively. First, you’ll explore optimal data collection methods. Next, you’ll discover how to integrate data from diverse sources. Finally, you’ll learn how to do data collection for predictive modeling. When you’re finished with this course, you’ll have the skills and knowledge of data collection techniques needed to execute various data science projects effectively

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What's inside

Syllabus

Course Overview
Understand Data Collection Techniques
Apply Data Collection Techniques

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a beginner-friendly foundation for data collection techniques
Focuses on effective data collection tailored to data science
Covers key methods and approaches for collecting data from diverse sources
Suitable for individuals seeking to enhance their understanding of data collection for predictive modeling

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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 Data Collection for Data Scientists with these activities:
Compile a list of data collection resources
Compiling a list of data collection resources will help you find the information you need to successfully collect data for your projects.
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  • Search the web for data collection resources.
  • Review the resources and select the ones that are most relevant to your needs.
  • Organize the resources into a list.
  • Share the list with your classmates.
Find a mentor who can provide guidance on data collection
Finding a mentor who can provide guidance on data collection will help you develop your skills more quickly and avoid common pitfalls.
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  • Identify the skills and knowledge that you want to develop.
  • Search for potential mentors who have those skills and knowledge.
  • Contact potential mentors and ask if they are interested in mentoring you.
  • Meet with your mentor regularly to discuss your progress and get feedback.
Read Data Science for Business
This book provides a comprehensive overview of data science and its applications in business, giving you a strong foundation for this course.
Show steps
  • Read chapters 1-3 to gain an understanding of the basics of data science.
  • Read chapters 4-6 to learn about data collection techniques.
  • Read chapters 7-9 to learn about data analysis techniques.
  • Read chapters 10-12 to learn about predictive modeling techniques.
Five other activities
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Discuss data collection techniques
Discussing data collection techniques with your classmates will help you learn from their experiences and perspectives.
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  • Find a group of classmates to discuss data collection techniques with.
  • Meet with your group regularly to discuss different data collection techniques.
  • Share your own experiences and perspectives on data collection.
  • Learn from the experiences and perspectives of your classmates.
Solve data collection problems
Solving data collection problems will help you develop your skills in identifying and gathering relevant data for your projects.
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  • Identify a problem that you want to solve using data.
  • Determine what data you need to collect to solve the problem.
  • Collect the data using appropriate techniques.
  • Analyze the data to identify trends and patterns.
  • Develop a solution to the problem based on your analysis.
Develop a data collection plan
Creating a data collection plan will help you organize your data collection process and ensure that you are collecting the right data.
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  • Define the goals of your data collection.
  • Identify the target population for your data collection.
  • Determine the data collection methods that you will use.
  • Develop a data collection schedule.
  • Create a data collection budget.
Participate in a data collection competition
Participating in a data collection competition will help you develop your skills in collecting and analyzing data.
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  • Find a data collection competition that you are interested in.
  • Register for the competition.
  • Collect data for the competition.
  • Analyze the data and develop a solution to the problem.
  • Submit your solution to the competition.
Mentor a junior data scientist
Mentoring a junior data scientist will help you solidify your understanding of data collection techniques and develop your leadership skills.
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  • Find a junior data scientist who is interested in your mentorship.
  • Meet with your mentee regularly to discuss their work and provide guidance.
  • Share your knowledge and experience with your mentee.
  • Help your mentee develop their skills in data collection.

Career center

Learners who complete Data Collection for Data Scientists will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist is a highly-skilled professional who uses statistical and computational techniques to extract insights from data. They use these findings to help businesses make better decisions. The course Data Collection for Data Scientists provides a solid foundation in the techniques used by Data Scientists to collect and analyze data. This training will especially help you if you are interested in working with data to build predictive models.
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to help businesses understand their customers and make better decisions. The course Data Collection for Data Scientists will help you develop the skills needed to succeed in this role, including data collection techniques, data integration, and data analysis.
Machine Learning Engineer
A Machine Learning Engineer is responsible for developing and deploying machine learning models to help businesses automate tasks and make better decisions. The course Data Collection for Data Scientists will help you build a foundation in the data collection techniques used by Machine Learning Engineers. This course will be especially helpful if you are interested in working with data to build predictive models.
Statistician
A Statistician is responsible for collecting, analyzing, and interpreting data to help businesses understand their customers and make better decisions. The course Data Collection for Data Scientists will help you develop the skills needed to succeed in this role, including data collection techniques, data integration, and data analysis.
Data Engineer
A Data Engineer is responsible for designing, building, and maintaining data pipelines to help businesses collect, store, and process data. The course Data Collection for Data Scientists will help you develop the skills needed to succeed in this role, including data collection techniques, data integration, and data analysis.
Business Analyst
A Business Analyst is responsible for understanding the business needs of an organization and developing solutions to meet those needs. The course Data Collection for Data Scientists may be useful for Business Analysts who want to learn more about data collection techniques.
Market Researcher
A Market Researcher is responsible for collecting and analyzing data to help businesses understand their customers and make better decisions. The course Data Collection for Data Scientists may be useful for Market Researchers who want to learn more about data collection techniques.
Product Manager
A Product Manager is responsible for overseeing the development and launch of new products. The course Data Collection for Data Scientists may be useful for Product Managers who want to learn more about data collection techniques.
Project Manager
A Project Manager is responsible for planning, executing, and closing projects. The course Data Collection for Data Scientists may be useful for Project Managers who want to learn more about data collection techniques.
Software Engineer
A Software Engineer is responsible for designing, developing, and testing software applications. The course Data Collection for Data Scientists may be useful for Software Engineers who want to learn more about data collection techniques.
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. The course Data Collection for Data Scientists may be useful for Database Administrators who want to learn more about data collection techniques.
Data Architect
A Data Architect is responsible for designing and building data architectures. The course Data Collection for Data Scientists may be useful for Data Architects who want to learn more about data collection techniques.
Data Scientist Manager
A Data Scientist Manager is responsible for leading and managing a team of Data Scientists. The course Data Collection for Data Scientists may be useful for Data Scientist Managers who want to learn more about data collection techniques.
Chief Data Officer
A Chief Data Officer is responsible for overseeing the data strategy of an organization. The course Data Collection for Data Scientists may be useful for Chief Data Officers who want to learn more about data collection techniques.
Data Science Consultant
A Data Science Consultant is responsible for providing data science consulting services to organizations. The course Data Collection for Data Scientists may be useful for Data Science Consultants who want to learn more about data collection techniques.

Reading list

We've selected seven 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 Data Collection for Data Scientists.
Provides a comprehensive overview of data collection techniques for data science, including data mining, web scraping, and social media data collection. It valuable resource for students and practitioners who want to learn more about data collection methods.
Provides a comprehensive overview of data mining techniques. It covers a wide range of topics, including data collection, data preprocessing, feature selection, and model evaluation.
Provides a simple guide to data analytics for beginners. It covers a wide range of topics, including data collection, data analysis, and data visualization.
Provides a guide to data collection and analysis for social science research. It covers a wide range of topics, including research design, data collection methods, and data analysis techniques.

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